Mila is a research institute in artificial intelligence which rallies 500 researchers specializing in the field of deep learning. Here is a directory of their publications, from 2018 to 2020.
2021-01
Explainability and Interpretability: Keys to Deep Medicine
Profiling Chromatin Landscape at High Resolution and Throughput with 2C-ChIP.
2020-12
Functional idiosyncrasy has a shared topography with group-level connectivity alterations in autism
The default network of the human brain is associated with perceived social isolation
Computing Nash equilibria for integer programming games.
Stochastic Damped L-BFGS with Controlled Norm of the Hessian Approximation
Decoding the neural dynamics of free choice in humans.
A Study of Condition Numbers for First-Order Optimization
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Team Optimal Control of Coupled Major-Minor Subsystems with Mean-Field Sharing
Historical and cross-disciplinary trends in the biological and social sciences reveal an accelerating adoption of advanced analytics
Intervention Design for Effective Sim2Real Transfer
Horizontal gene transfer and recombination analysis of SARS-CoV-2 genes helps discover its close relatives and shed light on its origin
Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual Representations.
Reinforcement Learning in Decentralized Stochastic Control Systems with Partial History Sharing.
Team-Optimal Solution of Finite Number of Mean-Field Coupled LQG Subsystems.
Team Optimal Control of Coupled Subsystems with Mean-Field Sharing.
Quantifying the effect of experimental perturbations at single-cell resolution
Autonomous navigation of stratospheric balloons using reinforcement learning.
StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling.
What matters and what is possible in neuroimaging meta-analyses (of psychopathy).
Task dependent deep LDA pruning of neural networks
Computer Vision and Image Understanding
(2020-12-01)
www.sciencedirect.com[Also on arXiv: Computer Vision and Pattern Recognition (2020-11-24)]Data-driven optimization model customization
2020-11
Histone H3.3G34-Mutant Interneuron Progenitors Co-opt PDGFRA for Gliomagenesis
Modeling assembly bias with machine learning and symbolic regression.
Universal Semantics for the Stochastic Lambda-Calculus.
Persistent Mixture Model Networks for Few-Shot Image Classification.
Gradient penalty from a maximum margin perspective.
arXiv: Learning
(2020-11-24)
Deep feature extraction of single-cell transcriptomes by generative adversarial network.
Multimodal dynamics modeling for off-road autonomous vehicles.
Geometry-Aware Universal Mirror-Prox.
On the Convergence of Continuous Constrained Optimization for Structure Learning.
An Effective Anti-Aliasing Approach for Residual Networks.
Weighted automata are compact and actively learnable.
Seeing Through your Skin: Recognizing Objects with a Novel Visuotactile Sensor.
Gradient Starvation: A Learning Proclivity in Neural Networks
Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease
Universal Dependencies 2.7
Approximate Minimization of Weighted Tree Automata
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers
Learned Equivariant Rendering without Transformation Supervision
Learning function from structure in neuromorphic networks
Unsupervised Learning of Dense Visual Representations.
Differentiation independent neuroprotective role of Vcan+ oligodendrocyte precursor cells in poststroke cognitive impairment recovery
On Posterior Collapse and Encoder Feature Dispersion in Sequence VAEs.
An Analysis of Dataset Overlap on Winograd-Style Tasks.
On Systematic Polarization-Adjusted Convolutional (PAC) Codes.
Affinity LCFCN: Learning to Segment Fish with Weak Supervision.
Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets.
NERO: A Biomedical Named-entity (Recognition) Ontology with a Large, Annotated Corpus Reveals Meaningful Associations Through Text Embedding
Patient, interrupted: MEG oscillation dynamics reveal temporal dysconnectivity in schizophrenia
Learning Efficient Task-Specific Meta-Embeddings with Word Prisms
Effectiveness of quarantine and testing to prevent COVID-19 transmission from arriving travelers
Learning to Handle Parameter Perturbations in Combinatorial Optimization: an Application to Facility Location
Urban Night Scenery Reconstruction by Day-night Registration and Synthesis.
Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model.
A note on the Lasserre hierarchy for different formulations of the maximum independent set problem
A Study of Policy Gradient on a Class of Exactly Solvable Models
Bisimulation metrics and norms for real-weighted automata
Towards a Comprehensive Taxonomy and Large-Scale Annotated Corpus for Online Slur Usage
Proceedings of the Fourth Workshop on Online Abuse and Harms
(2020-11-01)
An Empirical Investigation of Beam-Aware Training in Supertagging.
Learning Improvised Chatbots from Adversarial Modifications of Natural Language Feedback
Distilling Structured Knowledge for Text-Based Relational Reasoning
EMNLP 2020
(2020-11-01)
Structure Aware Negative Sampling in Knowledge Graphs
TESA: A Task in Entity Semantic Aggregation for Abstractive Summarization
EMNLP 2020
(2020-11-01)
Deconstructing word embedding algorithms
Factual Error Correction for Abstractive Summarization Models
TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles
EMNLP 2020
(2020-11-01)
Do sequence-to-sequence VAEs learn global features of sentences?
Recursive Top-Down Production for Sentence Generation with Latent Trees
Supervised Seeded Iterated Learning for Interactive Language Learning
2020-10
COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing
deep21: a Deep Learning Method for 21cm Foreground Removal
(venue unknown)
(2020-10-29)
Gaussian Process Bandit Optimization of theThermodynamic Variational Objective
$\texttt{deep21}$: a Deep Learning Method for 21cm Foreground Removal
Tensorpac: An open-source Python toolbox for tensor-based phase-amplitude coupling measurement in electrophysiological brain signals.
Task Similarity Estimation Through Adversarial Multitask Neural Network.
Optimization for Data-Driven Learning and Control
The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles
LEAD: Least-Action Dynamics for Min-Max Optimization
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks.
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation.
Efficient Learning in Non-Stationary Linear Markov Decision Processes.
The role of case importation in explaining differences in early SARS-CoV-2 transmission dynamics in Canada - a mathematical modeling study of surveillance data.
Assumptions about frequency-dependent architectures of complex traits bias measures of functional enrichment
Implicit Variational Inference: the Parameter and the Predictor Space
Predicting Infectiousness for Proactive Contact Tracing
Accelerating data filtering for database using FPGA
Neural Successive Cancellation Flip Decoding of Polar Codes
Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations
Stronger Transformers for Neural Multi-Hop Question Generation
In Search of Robust Measures of Generalization.
NU-GAN: High resolution neural upsampling with GAN
Explicitly Modeling Syntax in Language Model improves Generalization
Learning to Summarize Long Texts with Memory Compression and Transfer
Neural oscillations track natural but not artificial fast speech: Novel insights from speech-brain coupling using MEG
Optimising the Performance of Convolutional Neural Networks across Computing Systems using Transfer Learning
Cross-Modal Information Maximization for Medical Imaging: CMIM
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata.
Neural Approximate Sufficient Statistics for Implicit Models.
HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data
Connecting Weighted Automata, Tensor Networks and Recurrent Neural Networks through Spectral Learning
A recursive framework for predicting the time-course of drug sensitivity.
Approximate information state for approximate planning and reinforcement learning in partially observed systems.
Factual Error Correction for Abstractive Summarization Models
DoMoBOT: a bot for automated and interactive domain modelling.
The nonsmooth landscape of phase retrieval
Representation of Reinforcement Learning Policies in Reproducing Kernel Hilbert Spaces.
The Quadratic Multiknapsack Problem with Conflicts and Balance Constraints
Transparency and reproducibility in artificial intelligence.
Overheating-Avoidance Remapping Scheme for Reliability Enhancement of 3D PCM Storage Systems.
Parametric models for combined failure time data from an incident cohort study and a prevalent cohort study with follow-up.
GraphMix: Improved Training of GNNs for Semi-Supervised Learning.
Kidney injury molecule-1 is a potential receptor for SARS-CoV-2
An Empirical Investigation of Beam-Aware Training in Supertagging
Recursive Top-Down Production for Sentence Generation with Latent Trees.
Inference and Prediction Diverge in Biomedicine
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
Maximum Reward Formulation In Reinforcement Learning
Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function.
Regularized Inverse Reinforcement Learning
SACSANN: identifying sequence-based determinants of chromosomal compartments
TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix
Data-Driven Learning of Geometric Scattering Networks
Contact Graph Epidemic Modelling of COVID-19 for Transmission and Intervention Strategies.
Multi-Fact Correction in Abstractive Text Summarization.
Reward Propagation Using Graph Convolutional Networks
Reinforcement Learning with Random Delays
Supervised Seeded Iterated Learning for Interactive Language Learning.
Adversarial Boot Camp: label free certified robustness in one epoch.
Integrating Categorical Semantics into Unsupervised Domain Translation.
Incorporating Dynamic Flight Network in SEIR to Model Mobility between Populations
Optimization over Random and Gradient Probabilistic Pixel Sampling for Fast, Robust Multi-Resolution Image Registration
Uncertainty driven probabilistic voxel selection for image registration
Embedding for Anomaly Detection on Health Insurance Claims.
Multi-Fact Correction in Abstractive Text Summarization
NutriQuébec: a unique web-based prospective cohort study to monitor the population's eating and other lifestyle behaviours in the province of Québec.
Differentially Private Data Publishing for Arbitrarily Partitioned Data
Towards a Classification of Behavioural Equivalences in Continuous-time Markov Processes
Live Demonstration: Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate
A Regression-Based Method to Synthesize Complex Arithmetic Computations on Stochastic Streams
Towards Efficient On-Chip Learning using Equilibrium Propagation
Video Key Object Detection Network via Reinforcement Learning
Numeric Data Augmentation using Structural Constraint Wasserstein Generative Adversarial Networks
High-Throughput VLSI Architecture for GRAND
2020-09
Measuring Systematic Generalization in Neural Proof Generation with Transformers
Measuring Systematic Generalization in Neural Proof Generation with Transformers
Deep discriminant analysis for task-dependent compact network search
Out-of-Distribution Classification and Clustering
Mem2Mem: Learning to Summarize Long Texts with Memory Compression and Transfer
Graph Adversarial Networks: Protecting Information against Adversarial Attacks.
Flight-connection Prediction for Airline Crew Scheduling to Construct Initial Clusters for OR Optimizer.
Networked control of coupled subsystems: Spectral decomposition and low-dimensional solutions.
Sex-specific lesion topographies explain outcomes after acute ischemic stroke
Population variability in social brain morphology:links to socioeconomic status and health disparity
Fast greedy $$\mathcal {C}$$ C -bound minimization with guarantees
Structure Aware Negative Sampling in Knowledge Graphs
A Partially Ranked Choice Model for Large-Scale Data-Driven Assortment Optimization
Causal Inference for Recommender Systems
Global Surveillance of COVID-19 by mining news media using a multi-source dynamic embedded topic model
Accelerometer-based smartphone eavesdropping
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data.
Overfit Neural Networks as a Compact Shape Representation
Practical Dynamic SC-Flip Polar Decoders: Algorithm and Implementation
Predictive learning as a network mechanism for extracting low-dimensional latent space representations
Graph Representation Learning
Decoding Polar Codes with Reinforcement Learning
The Importance of Pessimism in Fixed-Dataset Policy Optimization
MLMLM: Link Prediction with Mean Likelihood Masked Language Model
Synbols: Probing Learning Algorithms with Synthetic Datasets
Synbols: Probing Learning Algorithms with Synthetic Datasets
Landmark-based Ensemble Learning with Random Fourier Features and Gradient Boosting
Stability of Decentralized Gradient Descent in Open Multi-Agent Systems
Adversarial score matching and improved sampling for image generation
An Empirical Study of Human Behavioral Agents in Bandits, Contextual Bandits and Reinforcement Learning.
Keynote Lecture Building Knowledge For AI AgentsWith Reinforcement Learning
Machine learning in airline crew pairing to construct initial clusters for dynamic constraint aggregation
Correction to: Why public health matters today and tomorrow: the role of applied public health research.
Canadian Journal of Public Health-revue Canadienne De Sante Publique
(2020-09-02)
www.ncbi.nlm.nih.govPDFChange Point Detection by Cross-Entropy Maximization.
SCG: Spotting Coordinated Groups in Social Media.
arXiv: Social and Information Networks
(2020-09-02)
Fixing Bias in Reconstruction-Based Anomaly Detection with Lipschitz Discriminators
Learning General Transformations of Data for Out-of-Sample Extensions
Traceability Network Analysis: A Case Study of Links in Issue Tracking Systems
2020 IEEE Seventh International Workshop on Artificial Intelligence for Requirements Engineering (AIRE)
(2020-09-01)
xplorestaging.ieee.orgSENET: A Semantic Web for Supporting Automation of Software Engineering Tasks
2020 IEEE Seventh International Workshop on Artificial Intelligence for Requirements Engineering (AIRE)
(2020-09-01)
xplorestaging.ieee.orgOn the Effectiveness of Two-Step Learning for Latent-Variable Models
VeRNAl: A Tool for Mining Fuzzy Network Motifs in RNA.
Machine Learning in Airline Crew Pairing to Construct Initial Clusters for Dynamic Constraint Aggregation
Disentangling presentation and processing times in the brain
2020-08
Biomedical Image Analysis Challenges (BIAS) Reporting Guideline
Beyond variance reduction: Understanding the true impact of baselines on policy optimization
Reinforcement Learning Based Penetration Testing of a Microgrid Control Algorithm.
Analyzing the Resiliency of Microgrid Control Algorithms Against Malicious Input
BDD-based optimization for the quadratic stable set problem
Information correspondence between types of documentation for APIs
Robustesse structurelle des architectures d'apprentissage profond
Beyond brain age: Empirically-derived proxy measures of mental health
Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets.
Generative lesion pattern decomposition of cognitive impairment after stroke
How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics
Laplacian Change Point Detection for Dynamic Graphs.
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation
Precision, Equity, and Public Health and Epidemiology Informatics - A Scoping Review.
BIAS: Transparent reporting of biomedical image analysis challenges
Action-Based Representation Learning for Autonomous Driving
Partitioning gene-based variance of complex traits by gene score regression.
Do Syntax Trees Help Pre-trained Transformers Extract Information?
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks.
A Framework for Studying Reinforcement Learning and Sim-to-Real in Robot Soccer
Fast reinforcement learning with generalized policy updates
Proceedings of the National Academy of Sciences of the United States of America
(2020-08-17)
syndication.highwire.orgA review of the-state-of-the-art in data-driven approaches for building energy prediction
Restless bandits: indexability and computation of Whittle index
Introduction to Dynamic Stochastic Computing
Prediction, Not Association, Paves the Road to Precision Medicine
Adaptive Tensor Learning with Tensor Networks
Meta-matching: a simple framework to translate phenotypic predictive models from big to small data
DeepDrummer : Generating Drum Loops using Deep Learning and a Human in the Loop.
When Are Search Completion Suggestions Problematic
Deep Generative Models for Galaxy Image Simulations
Heterogeneous data release for cluster analysis with differential privacy
Machine Learning for Combinatorial Optimization: a Methodological Tour d’Horizon
European Journal of Operational Research
(2020-08-08)
www.sciencedirect.comPDF[Also on arXiv preprint arXiv:1811.06128 (2018-11-15)]Hidden population modes in social brain morphology: Its parts are more than its sum
Statistical Evidence for Learnable Lexical Subclasses in Japanese
Distinct miRNA Profile of Cellular and Extracellular Vesicles Released from Chicken Tracheal Cells Following Avian Influenza Virus Infection.
SeroTracker: a global SARS-CoV-2 seroprevalence dashboard.
Dimensionality and flexibility of learning in biological recurrent neural networks
Implicit Regularization in Deep Learning: A View from Function Space
A Neural Network Based Approach to Domain Modelling Relationships and Patterns Recognition
2020 IEEE Tenth International Model-Driven Requirements Engineering (MoDRE)
(2020-08-01)
xplorestaging.ieee.orgTowards Queryable and Traceable Domain Models
Dynamic planning of redundant robots within a set-based task-priority inverse kinematics framework
Myeloarchitecture gradients in the human insula: Histological underpinnings and association to intrinsic functional connectivity.
Optimal Local and Remote Controllers With Unreliable Uplink Channels: An Elementary Proof
Renewal Monte Carlo: Renewal Theory-Based Reinforcement Learning
A multicut outer-approximation approach for competitive facility location under random utilities
Leveraging cluster backbones for improving MAP inference in statistical relational models
2020-07
Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence
Population variability in social brain morphology for social support, household size and friendship satisfaction
Inferring disease subtypes from clusters in explanation space.
Patterns of autism symptoms: hidden structure in the ADOS and ADI-R instruments.
Deriving Differential Target Propagation from Iterating Approximate Inverses
Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning
La-MAML: Look-ahead Meta Learning for Continual Learning
Are Few-Shot Learning Benchmarks too Simple ? Solving them without Task Supervision at Test-Time.
arXiv: Learning
(2020-07-27)
Analyzing and Learning from User Interactions for Search Clarification
Operationalizing the Legal Principle of Data Minimization for Personalization
BabyAI 1.1.
Importation of SARS-CoV-2 following the "semaine de relache" and Quebec's (Canada) COVID-19 burden - a mathematical modeling study
Phenotypical predictors of Restless Legs Syndrome in pregnancy and their association with basal ganglia and the limbic circuits
Learning the Latent Space of Robot Dynamics for Cutting Interaction Inference.
HInet: Generating neutral hydrogen from dark matter with neural networks
Neuronal activity remodels the F-actin based submembrane lattice in dendrites but not axons of hippocampal neurons
Slot Contrastive Networks: A Contrastive Approach for Representing Objects.
Neurocognitive patterns dissociating semantic processing from executive control are linked to more detailed off-task mental time travel.
GRADE: Graph Dynamic Embedding.
Molecular signatures of cognition and affect
High-Throughput VLSI Architecture for GRAND.
Extendable and invertible manifold learning with geometry regularized autoencoders.
Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP
Building reproducible, reusable, and robust machine learning software.
S2RMs: Spatially Structured Recurrent Modules.
What can I do here? A Theory of Affordances in Reinforcement Learning
On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings
All in the (Exponential) Family: Information Geometry and Thermodynamic Variational Inference
FDG-PET/CT Radiomics Models for The Early Prediction of Loco-regional Recurrence in Head and Neck Cancer
Vision-Based Goal-Conditioned Policies for Underwater Navigation in the Presence of Obstacles
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
Representations for Stable Off-Policy Reinforcement Learning
An end-to-end approach for the verification problem: learning the right distance
Universal Equivariant Multilayer Perceptrons
Latent Variable Modelling with Hyperbolic Normalizing Flows
Inductive Relation Prediction by Subgraph Reasoning
On Variational Learning of Controllable Representations for Text without Supervision
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay.
Constrained Markov Decision Processes via Backward Value Functions
Invariant Causal Prediction for Block MDPs
Online Learned Continual Compression with Adaptive Quantization Modules
Interference and Generalization in Temporal Difference Learning
Few-shot Relation Extraction via Bayesian Meta-learning on Task Graphs
Continuous Graph Neural Networks
A Graph to Graphs Framework for Retrosynthesis Prediction
Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling
Linear Lower Bounds and Conditioning of Differentiable Games
Stochastic Hamiltonian Gradient Methods for Smooth Games
Data-Efficient Reinforcement Learning with Momentum Predictive Representations
Countering Language Drift with Seeded Iterated Learning
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
Learning to Navigate in Synthetically Accessible Chemical Space Using Reinforcement Learning
Revisiting Fundamentals of Experience Replay
Small-GAN: Speeding up GAN Training using Core-Sets
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Perceptual Generative Autoencoders
Feature Statistics Guided Efficient Filter Pruning
Augmented base pairing networks encode RNA-small molecule binding preferences.
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks
SVRG for Policy Evaluation with Fewer Gradient Evaluations
Generative Graph Perturbations for Scene Graph Prediction.
On the Social and Technical Challenges of Web Search Autosuggestion Moderation.
Learning Graph Structure With A Finite-State Automaton Layer.
Robust motion in-betweening
Using Deep Learning to Accelerate Knee MRI at 3T: Results of an Interchangeability Study.
Superior breast cancer metastasis risk stratification using an epithelial-mesenchymal-amoeboid transition gene signature.
Directional sources and listeners in interactive sound propagation using reciprocal wave field coding
A Weakly Supervised Region-Based Active Learning Method for COVID-19 Segmentation in CT Images.
3D Shape Reconstruction from Vision and Touch.
The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning.
Sharp Analysis of Smoothed Bellman Error Embedding.
Comparing Audience Appreciation to Fact-Checking Across Political Communities on Reddit.
TimelyRep: Timing deterministic replay for Android web applications
Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System.
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
Probing Linguistic Systematicity
Words aren’t enough, their order matters: On the Robustness of Grounding Visual Referring Expressions
Learning an Unreferenced Metric for Online Dialogue Evaluation
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs
Interactive Machine Comprehension with Information Seeking Agents
Would you Rather? A New Benchmark for Learning Machine Alignment with Cultural Values and Social Preferences
Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach
A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images.
Deep interpretability for GWAS
Differentiable Causal Discovery from Interventional Data.
A network-informed analysis of SARS-CoV-2 and hemophagocytic lymphohistiocytosis genes' interactions points to Neutrophil Extracellular Traps as mediators of thrombosis in COVID-19
Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs.
Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
Laplacian Change Point Detection for Dynamic Graphs.
Survey on Applications of Multi-Armed and Contextual Bandits
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference.
Counterexamples on the Monotonicity of Delay Optimal Strategies for Energy Harvesting Transmitters
Bringing proportional recovery into proportion: Bayesian modelling of post-stroke motor impairment.
Hemispheric specialization within the inferior parietal lobe across cognitive domains
Practical Product Path Guiding Using Linearly Transformed Cosines
Five Ways in Which Computational Modeling Can Help Advance Cognitive Science: Lessons From Artificial Grammar Learning.
Legends: Folklore on Reddit.
Accelerating Deep Learning Systems via Critical Set Identification and Model Compression
EvoLSTM: context-dependent models of sequence evolution using a sequence-to-sequence LSTM.
Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions.
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract).
Adversarial Example Games.
Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition.
The need for privacy with public digital contact tracing during the COVID-19 pandemic
2020-06
Semi-supervised Sequential Generative Models.
Leveraging Subword Embeddings for Multinational Address Parsing
Medical Imaging with Deep Learning: MIDL 2020 - Short Paper Track.
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems
Learning to Fix Build Errors with Graph2Diff Neural Networks
Machine learning analysis identifies genes differentiating triple negative breast cancers.
Hybrid Models for Learning to Branch.
On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools
Inherent privacy limitations of decentralized contact tracing apps.
Shared and unique brain network features predict cognition, personality and mental health in childhood
Advances in Asynchronous Parallel and Distributed Optimization
Graph Policy Network for Transferable Active Learning on Graphs
gRemote: API-Forwarding Powered Cloud Rendering.
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
Rethinking Distributional Matching Based Domain Adaptation.
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer
Advantages of biologically-inspired adaptive neural activation in RNNs during learning.
Revisiting Loss Modelling for Unstructured Pruning.
HNHN: Hypergraph Networks with Hyperedge Neurons.
A Universal Representation Transformer Layer for Few-Shot Image Classification.
Learning to Prove from Synthetic Theorems.
An operator view of policy gradient methods.
The causes and consequences of COVID-19 misperceptions: understanding the role of news and social media
Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations.
Improving Few-Shot Visual Classification with Unlabelled Examples.
Learning Lexical Subspaces in a Distributional Vector Space
Intelligent Tools for Precision Public Health.
Untangling tradeoffs between recurrence and self-attention in neural networks
Gradient Estimation with Stochastic Softmax Tricks
Cross-layer communication over fading channels with adaptive decision feedback
Design and implementation of a modular interior-point solver for linear optimization
Supervised Visualization for Data Exploration
Gradient Estimation with Stochastic Softmax Tricks
Decoding the neural dynamics of free choice in humans
Improved Few-Shot Visual Classification
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence.
PatchUp: A Regularization Technique for Convolutional Neural Networks
Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings.
Deep Reinforcement and InfoMax Learning.
A Brief Look at Generalization in Visual Meta-Reinforcement Learning
Learning Causal Models Online.
To Each Optimizer a Norm, To Each Norm its Generalization.
Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search).
Learning normalizing flows from Entropy-Kantorovich potentials
Deterministic Gaussian Averaged Neural Networks.
Standardised convolutional filtering for radiomics.
Delayed Rejection Metropolis Light Transport
On Generalized Surrogate Duality in Mixed-Integer Nonlinear Programming
Provable Guarantees for General Two-sided Sequential Matching Markets
Dissociating memory accessibility and precision in forgetting.
Adversarial Feature Desensitization.
Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge
Magnetic Resonance in Medicine
(2020-06-07)
nyuscholars.nyu.eduPDF[Also on arXiv preprint arXiv:2001.02518 (2020-01-06)]NeuroPycon: An open-source python toolbox for fast multi-modal and reproducible brain connectivity pipelines.
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias
Dark control: The default mode network as a reinforcement learning agent.
Shapley Homology: Topological Analysis of Sample Influence for Neural Networks.
Neural Computation
(2020-06-05)
www.mitpressjournals.orgPDF[Also on arXiv preprint arXiv:1910.06509 (2019-10-15)]Equivariant Maps for Hierarchical Structures.
Santé publique de précision : Rêve ou réalité?
Precision public health: Dream or reality?
Codon arrangement modulates MHC-I peptides presentation
Operation Merging for Hardware Implementations of Fast Polar Decoders
A principled approach for generating adversarial images under non-smooth dissimilarity metrics
The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.
Deep Active Learning: Unified and Principled Method for Query and Training
AISTATS 2020
(2020-06-03)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1911.09162 (2019-11-20)]Old Dog Learns New Tricks: Randomized UCB for Bandit Problems
The Neurobiology of Social Distance.
LAMPS: an analysis pipeline for sequence-specific ligation-mediated amplification reads.
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation.
AISTATS 2020
(2020-06-03)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1910.04920 (2019-10-11)]Bayesian Neural Networks
Surprisal-Triggered Conditional Computation with Neural Networks
Tabu search for the time-dependent vehicle routing problem with time windows on a road network
Training End-to-End Analog Neural Networks with Equilibrium Propagation.
Graph Policy Network for Transferable Active Learning on Graphs
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
Restless bandits: Indexability and computation of Whittle index
Machine and deep learning methods for radiomics.
Fast Thresholded SC-Flip Decoding of Polar Codes
VoronoiNet: General Functional Approximators With Local Support
Human Anterior Insula Encodes Performance Feedback and Relays Prediction Error to the Medial Prefrontal Cortex
A tutorial on recursive models for analyzing and predicting path choice behavior
EURO Journal on Transportation and Logistics
(2020-06-01)
www.sciencedirect.com[Also on arXiv preprint arXiv:1905.00883 (2019-05-02)]Machine Learning for COVID-19 needs global collaboration and data-sharing
CLAREL: classification via retrieval loss for zero-shot learning
Multi-Image Super-Resolution for Remote Sensing Using Deep Recurrent Networks
2020-05
An ILP Model for Multi-Label MRFs With Connectivity Constraints
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning
Self-supervised Robust Object Detectors from Partially Labelled datasets.
Minimisation in Logical Form.
Inferring multimodal latent topics from electronic health records
Failure to follow medication changes made at hospital discharge is associated with adverse events in 30 days
Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis.
An Analysis of the Adaptation Speed of Causal Models
COVI White Paper.
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation.
De-Aliasing States In Dialogue Modelling With Inverse Reinforcement Learning
Universal Dependencies 2.6
Predictive Pattern Classification Can Distinguish Gender Identity Subtypes from Behavior and Brain Imaging.
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks
Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks
RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy via Deep Learning.
Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach
Study of Restrained Network Structures for Wasserstein Generative Adversarial Networks (WGANs) on Numeric Data Augmentation
Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL
Modeling Route Choice with Real-Time Information: Comparing the Recursive and Non-Recursive Models.
Young Chinese Consumers’ Choice between Product-Related and Sustainable Cues—The Effects of Gender Differences and Consumer Innovativeness
Decoupling of Gd–Cr magnetism and giant magnetocaloric effect in layered honeycomb tellurate GdCrTeO6
TRACKING AND PREDICTING COVID-19 RADIOLOGICAL TRAJECTORY USING DEEP LEARNING ON CHEST X-RAYS: INITIAL ACCURACY TESTING
Lookahead Converges to Stationary Points of Smooth Non-convex Functions
Deep Geometric Knowledge Distillation with Graphs
ICASSP 2020
(2020-05-04)
hal.archives-ouvertes.frPDF[Also on arXiv preprint arXiv:1911.03080 (2019-11-08)]View-Invariant Loop Closure with Oriented Semantic Landmarks
∇SLAM: Dense SLAM meets Automatic Differentiation
RISC-V Barrel Processor for Accelerator Control
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well
In-Hardware Training Chip Based on CMOS Invertible Logic for Machine Learning
Simplified Dynamic SC-Flip Polar Decoding
Remote Estimation Over a Packet-Drop Channel With Markovian State
General Principles of Gene Dosage Effects on Brain Structure
What Can Machine Learning Do for Psychiatry
An Efficient Transport Estimator for Complex Layered Materials
Local Bases for Model‐reduced Smoke Simulations
Using Speech Synthesis to Train End-To-End Spoken Language Understanding Models
$${\textsf {SecDM}}$$SecDM: privacy-preserving data outsourcing framework with differential privacy
Pre-trained CNNs as Visual Feature Extractors: A Broad Evaluation
Depth Prediction for Monocular Direct Visual Odometry
Machine-learning-based column selection for column generation
Route choice behaviour and travel information in a congested network: Static and dynamic recursive models
Systems consolidation impairs behavioral flexibility.
HipoRank: Incorporating Hierarchical and Positional Information into Graph-based Unsupervised Long Document Extractive Summarization
2020-04
Locality and Compositionality in Zero-Shot Learning
SYSTEM AND METHOD FOR CROSS-DOMAIN TRANSFERABLE NEURAL COHERENCE MODEL
SloMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
Autism spectrum heterogeneity: fact or artifact?
LEARNING EXECUTION THROUGH NEURAL CODE FUSION
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Conditional Learning of Fair Representations
Spike-based causal inference for weight alignment
On the interaction between supervision and self-play in emergent communication
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Language GANs Falling Short
Reinforced active learning for image segmentation
Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents
Gradient-Based Neural DAG Learning
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
On Bonus Based Exploration Methods In The Arcade Learning Environment
Learning the Arrow of Time for Problems in Reinforcement Learning
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives
Deep feature extraction of single-cell transcriptomes by generative adversarial network
Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation.
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning
sistemas e métodos para realizar otimização bayesiana
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning
Evaluating Stochastic Rankings with Expected Exposure
Travel speed prediction based on learning methods for home delivery
Interpretable Neuron Structuring with Graph Spectral Regularization
Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
General Cops and Robbers Games with randomness.
Decentralized linear quadratic systems with major and minor agents and non-Gaussian noise
Preface to the special issue of INFOR on “continuous optimization and applications in machine learning and data analytics”
Predictive inference for travel time on transportation networks.
Prediction intervals for travel time on transportation networks
Glossary for public health surveillance in the age of data science
Inference for travel time on transportation networks
ArguLens: Anatomy of Community Opinions On Usability Issues Using Argumentation Models.
Experience Grounds Language
Meta-analytic evidence for a joint neural mechanism underlying response inhibition and state anger.
ArguLens: Anatomy of Community Opinions On Usability Issues Using Argumentation Models.
The Covering-Assignment Problem for Swarm-powered Ad-hoc Clouds: A Distributed 3D Mapping Use-case
Experience Grounds Language
StereoSet: Measuring stereotypical bias in pretrained language models
Role-Wise Data Augmentation for Knowledge Distillation
Tensorpac : an open-source Python toolbox for tensor-based Phase-Amplitude Coupling measurement in electrophysiological brain signals
Neuropsychiatric copy number variants exert shared effects on human brain structure
A Rare Moment of Cross-Partisan Consensus: Elite and Public Response to the COVID-19 Pandemic in Canada
Do sequence-to-sequence VAEs learn global features of sentences?
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
Analysing brain networks in population neuroscience: a case for the Bayesian philosophy
Hierarchical Bayesian Optimization of Spatiotemporal Neurostimulations for Targeted Motor Outputs
Learning to Drive Off Road on Smooth Terrain in Unstructured Environments Using an On-Board Camera and Sparse Aerial Images
Learning to Drive Off Road on Smooth Terrain in Unstructured Environments Using an On-Board Camera and Sparse Aerial Images
Establishing an evaluation metric to quantify climate change image realism
Machine Learning: Science and Technology
(2020-04-09)
dblp.uni-trier.de[Also on arXiv preprint arXiv:1910.10143 (2019-10-22)]Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists.
Can EEG and MEG detect signals from the human cerebellum
CNN Detection of New and Enlarging Multiple Sclerosis Lesions from Longitudinal Mri Using Subtraction Images
Gifting in Multi-Agent Reinforcement Learning (Student Abstract).
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract)
Combating False Negatives in Adversarial Imitation Learning (Student Abstract)
BigBrain 3D atlas of cortical layers: Cortical and laminar thickness gradients diverge in sensory and motor cortices.
Fast protein database as a service with kAAmer
Learning to cooperate: Emergent communication in multi-agent navigation.
The Covering-Assignment Problem for Swarm-powered Ad-hoc Clouds: A Distributed 3D Mapping Use-case
Decision letter: Population coupling predicts the plasticity of stimulus responses in cortical circuits
Machine learning-based models of sawmills for better wood allocation planning
High-Throughput Low-Latency Encoder and Decoder for a Class of Generalized Reed–Solomon Codes for Short-Reach Optical Communications
GitHub Repositories with Links to Academic Papers: Open Access, Traceability, and Evolution.
Leveraging Historical Associations between Requirements and Source Code to Identify Impacted Classes
The Covering-Assignment Problem for Swarm-powered Ad-hoc Clouds: A Distributed 3D Mapping Use-case
Integrated integer programming and decision diagram search tree with an application to the maximum independent set problem
MapLite: Autonomous Intersection Navigation Without a Detailed Prior Map
Distinct roles of parvalbumin and somatostatin interneurons in gating the synchronization of spike times in the neocortex.
2020-03
Both New and Chronic Potentially Inappropriate Medications Continued at Hospital Discharge Are Associated With Increased Risk of Adverse Events.
Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits
Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation
Planning as Inference in Epidemiological Models.
Coping With Simulators That Don't Always Return
Countering Language Drift with Seeded Iterated Learning.
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)
Multi-scale network regression for brain-phenotype associations.
On-the-Fly Adaptation of Source Code Models using Meta-Learning
Learning to Play Soccer by Reinforcement and Applying Sim-to-Real to Compete in the Real World
One-Shot Informed Robotic Visual Search in the Wild
Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images Using a View-Based Representation
Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images Using a View-Based Representation
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks.
Object-Centric Image Generation from Layouts.
Structural and developmental principles of neuropil assembly in C. elegans
Evaluating Logical Generalization in Graph Neural Networks.
On the Morality of Artificial Intelligence [Commentary]
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning.
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
Inter-dependent Centrosomal Co-localization of the cen and ik2 cis-Natural Antisense mRNAs in Drosophila
DIBS: Diversity inducing Information Bottleneck in Model Ensembles.
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift.
The Residence History Inference Problem.
Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces
Stable Policy Optimization via Off-Policy Divergence Regularization.
Continuous Domain Adaptation with Variational Domain-Agnostic Feature Replay
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control
Not one model fits all: unfairness in RSFC-based prediction of behavioral data in African American
Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features.
Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features.
Frontiers in Bioengineering and Biotechnology
(2020-03-03)
www.frontiersin.org[Also on arXiv preprint arXiv:1912.00283 (2019-11-30)]A cross-national study of young female consumer behaviour, innovativeness and apparel evaluation: China and India
Curriculum By Texture.
Asynchronous Gradient-Push
Tensor Networks for Language Modeling.
RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning.
Tensor Networks for Probabilistic Sequence Modeling
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Benchmarking Graph Neural Networks
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning
Probabilistic Sequential Multi-Objective Optimization of Convolutional Neural Networks
10,000 social brains: sex differentiation in human brain anatomy
Systematic approach to provide building occupants with feedback to reduce energy consumption
Detecting breaking news rumors of emerging topics in social media
Joint location and pricing within a user-optimized environment
The Hanabi Challenge: A New Frontier for AI Research
Multiple Kernel Learning-Based Transfer Regression for Electric Load Forecasting
2020-02
Machine Learning Analysis of Exome Trios to Contrast the Genomic Architecture of Autism and Schizophrenia
The importance of transparency and reproducibility in artificial intelligence research
PAC-Bayes and Domain Adaptation
On Catastrophic Interference in Atari 2600 Games
Policy Evaluation Networks.
Solving ODE with Universal Flows: Approximation Theory for Flow-Based Models
Fasting alters the gut microbiome with sustained blood pressure and body weight reduction in metabolic syndrome patients
RADICL-seq identifies general and cell type-specific principles of genome-wide RNA-chromatin interactions
Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence.
Automatic Generation of Specialized Direct Convolutions for Mobile GPUs
Generating Fast Sparse Matrix Vector Multiplication From a High Level Generic Functional IR
High-level hardware feature extraction for GPU performance prediction of stencils
Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games.
Learning Dynamic Belief Graphs to Generalize on Text-Based Games.
oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions.
Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning
Improving Policy-Capturing with Active Learning for Real-Time Decision Support
The Geometry of Sign Gradient Descent
Curriculum in Gradient-Based Meta-Reinforcement Learning.
Generating Automatic Curricula via Self-Supervised Active Domain Randomization.
Binary Ostensibly‐Implicit Trees for Fast Collision Detection
Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models.
Latent Variable Modelling with Hyperbolic Normalizing Flows
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery
DeepFood: Food Image Analysis and Dietary Assessment via Deep Model
Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies
Team Optimal Decentralized State Estimation of Linear Stochastic Processes by Agents with Non-Classical Information Structures.
Modeling Cloud Reflectance Fields using Conditional Generative Adversarial Networks
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization.
Input Dropout for Spatially Aligned Modalities
Modeling Dialogues with Hashcode Representations: A Nonparametric Approach
Input Dropout for Spatially Aligned Modalities
Improved PAC-Bayesian Bounds for Linear Regression
Memory Augmented Graph Neural Networks for Sequential Recommendation
Learning General Latent-Variable Graphical Models with Predictive Belief Propagation
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking
Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning
Options of Interest: Temporal Abstraction with Interest Functions
Provably efficient reconstruction of policy networks.
Detecting semantic anomalies
Meta-learning framework with applications to zero-shot time-series forecasting
Exploring Structural Inductive Biases in Emergent Communication.
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation
Deep Learning Techniques for Decoding Polar Codes
Replication Packager for 'Generating Fast Sparse Matrix Vector Multiplicationfrom a High Level Generic Functional IR'
Combating False Negatives in Adversarial Imitation Learning.
Machine learning in airline crew pairing to construct initial clusters for dynamic constraint aggregation
An Efficient Software Stack Sphere Decoder for Polar Codes
Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics.
Catalytic hydrolysis of microcystin-LR peptides on the surface of naturally occurring minerals
Efficient drone hijacking detection using two-step GA-XGBoost
Assessment of Extubation Readiness Using Spontaneous Breathing Trials in Extremely Preterm Neonates.
2020-01
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning.
A white-light-emitting single MOF sensor-based array for berberine homologue discrimination
The Indian Chefs Process.
fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning.
A luminescent MOF as a fluorescent sensor for the sequential detection of Al3+ and phenylpyruvic acid
Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate.
Using Simulated Data to Generate Images of Climate Change
Uncertainty Evaluation Metric for Brain Tumour Segmentation.
Medical Imaging with Deep Learning
(2020-01-25)
dblp.uni-trier.dePDF[LATEST on arXiv preprint arXiv:2005.14262 (2020-05-28)]Multi-Task Self-Supervised Learning for Robust Speech Recognition
Towards Graph Representation Learning in Emergent Communication
SafeWatch: A Wearable Hand Motion Tracking System for Improving Driving Safety
Optogenetic activation of parvalbumin and somatostatin interneurons selectively restores theta-nested gamma oscillations and oscillation-induced spike timing-dependent long-term potentiation impaired by amyloid β oligomers
Ultrasensitive Assay of Alkaline Phosphatase Based on the Fluorescent Response Difference of the Metal-Organic Framework Sensor.
HIFI: estimating DNA-DNA interaction frequency from Hi-C data at restriction-fragment resolution
Uncovering axes of variation among single-cell cancer specimens.
Tiling Optimizations for Stencil Computations Using Rewrite Rules in Lift
Partitioning gene-based variance of complex traits by gene score regression
Internal representation dynamics and geometry in recurrent neural networks.
Upstream ORF-Encoded ASDURF Is a Novel Prefoldin-like Subunit of the PAQosome.
Author Correction: Visualizing structure and transitions in high-dimensional biological data.
Authorship Analysis Approaches
Cybersecurity And Cybercrime Investigation
Authorship Attribution With Few Training Samples
Writeprint Mining For Authorship Attribution
Artificial Intelligence And Digital Forensics
Machine Learning for Authorship Attribution and Cyber Forensics
Criminal Information Mining
Messaging Forensics In Perspective
Analyzing Network Level Information
You could have said that instead: Improving Chatbots with Natural Language Feedback.
Plan2Vec: Unsupervised Representation Learning by Latent Plans
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective
Learning Inter-Modal Correspondence and Phenotypes from Multi-Modal Electronic Health Records
IEEE Transactions on Knowledge and Data Engineering
(2020-01-01)
xplorestaging.ieee.org[LATEST on arXiv preprint arXiv:2011.06301 (2020-11-12)]3D Shape Reconstruction from Vision and Touch
Hybrid Models for Learning to Branch
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
Look-ahead Meta Learning for Continual Learning
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
An operator view of policy gradient methods
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
Learning Graph Structure With A Finite-State Automaton Layer
Curriculum By Smoothing
Deep Reinforcement and InfoMax Learning
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation
Untangling tradeoffs between recurrence and self-attention in artificial neural networks
Forethought and Hindsight in Credit Assignment
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay
Reward Propagation Using Graph Convolutional Networks
On Efficiency in Hierarchical Reinforcement Learning
Value-driven Hindsight Modelling
Novelty Search in Representational Space for Sample Efficient Exploration
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning
In search of robust measures of generalization
Differentiable Causal Discovery from Interventional Data
Adversarial Example Games
Unsupervised Learning of Dense Visual Representations
Learning-based Practical Smartphone Eavesdropping with Built-in Accelerometer.
Acquiring and Predicting Multidimensional Diffusion (MUDI) Data: An Open Challenge
Double-Linear Thompson Sampling for Context-Attentive Bandits.
Semi-supervised Sequential Generative Models.
Unsupervised Domain Adversarial Self-Calibration for Electromyographic-based Gesture Recognition.
The Indian Chefs Process.
Stable Policy Optimization via Off-Policy Divergence Regularization.
Exploiting Link Diversity for Performance-Aware and Repeatable Simulation in Low-Power Wireless Networks
Lessons in resilience: Canada's digital media ecosystem and the 2019 election
Shaping the Narrative Arc: Information-Theoretic Collaborative Dialogue
(venue unknown)
(2020-01-01)
Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents
META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation.
Autonomous Agents and Multi-Agent Systems
(2020-01-01)
dblp.uni-trier.de[LATEST on arXiv: Learning (2020-05-18)]Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators
Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models.
Coping With Simulators That Don't Always Return.
Enabling Secure Trustworthiness Assessment and Privacy Protection in Integrating Data for Trading Person-Specific Information
Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation.
Efficient and Effective Dimension Control in Automotive Applications
AdSherlock: Efficient and Deployable Click Fraud Detection for Mobile Applications
Givs: Fine-Grained Gesture Control for Mobile Devices in Driving Environments
Bulk Savings for Bulk Transfers: Minimizing the Energy-Cost for Geo-Distributed Data Centers
How Do Open Source Software Contributors Perceive and Address Usability? Valued Factors, Practices, and Challenges
Mycorrhiza: Genotype Assignment using Phylogenetic Networks.
Activation Adaptation in Neural Networks.
Block planning for intermodal rail: Methodology and case study
The AI Driving Olympics at NeurIPS 2018
Few-Shot Learning
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms.
Exploring the Limits of Simple Learners in Knowledge Distillation for Document Classification with DocBERT.
Investigating the Influence of Selected Linguistic Features on Authorship Attribution using German News Articles.
Gifting in Multi-Agent Reinforcement Learning.
Value Preserving State-Action Abstractions.
A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry.
Tensorized Random Projections.
AISTATS 2020
(2020-01-01)
proceedings.mlr.press[LATEST on arXiv preprint arXiv:2003.05101 (2020-03-11)]GAIT: A Geometric Approach to Information Theory.
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games.
Accelerating Smooth Games by Manipulating Spectral Shapes.
AISTATS 2020
(2020-01-01)
proceedings.mlr.press[LATEST on arXiv preprint arXiv:2001.00602 (2020-01-02)]On the interplay between noise and curvature and its effect on optimization and generalization.
Toward Training Recurrent Neural Networks for Lifelong Learning.
Compositional Generalization by Factorizing Alignment and Translation.
2019-12
Forgetting at biologically realistic levels of neurogenesis in a large-scale hippocampal model.
Learning from Learning Machines: Optimisation, Rules, and Social Norms
On the Morality of Artificial Intelligence.
Unsupervised Domain Adversarial Self-Calibration for Electromyographic-based Gesture Recognition.
Clusters in Explanation Space: Inferring disease subtypes from model explanations.
A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs.
A learning-based algorithm to quickly compute good primal solutions for Stochastic Integer Programs.
Virtual Reality to Study the Gap Between Offline and Real-Time EMG-based Gesture Recognition
Joint Learning of Generative Translator and Classifier for Visually Similar Classes
Shaping representations through communication: community size effect in artificial learning systems
CLOSURE: Assessing Systematic Generalization of CLEVR Models.
ViGIL@NeurIPS
(2019-12-12)
ui.adsabs.harvard.eduPDF[Also on arXiv preprint arXiv:1912.05783 (2019-12-12)]Associative Alignment for Few-shot Image Classification
Associative Alignment for Few-shot Image Classification
Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning.
Marginalized State Distribution Entropy Regularization in Policy Optimization
Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods
Automated segmentation of cortical layers in BigBrain reveals divergent cortical and laminar thickness gradients in sensory and motor cortices.
Inherent Tradeoffs in Learning Fair Representation
The Option Keyboard: Combining Skills in Reinforcement Learning
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Hindsight Credit Assignment
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
The Thermodynamic Variational Objective
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
A Geometric Perspective on Optimal Representations for Reinforcement Learning
Learning Representations by Maximizing Mutual Information Across Views
Learning Neural Networks with Adaptive Regularization
Towards modular and programmable architecture search
Efficient Graph Generation with Graph Recurrent Attention Networks
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning
Probabilistic Logic Neural Networks for Reasoning
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
Online Continual Learning with Maximal Interfered Retrieval
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Real-Time Reinforcement Learning
Neural Multisensory Scene Inference
Reducing the variance in online optimization by transporting past gradients
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks
Reducing Noise in GAN Training with Variance Reduced Extragradient
Ordered Memory
No-Press Diplomacy: Modeling Multi-Agent Gameplay
On Adversarial Mixup Resynthesis
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets
Variational Temporal Abstraction
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Gradient based sample selection for online continual learning
Unsupervised State Representation Learning in Atari
Wasserstein Dependency Measure for Representation Learning
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
Disjunctive cuts for Mixed-Integer Conic Optimization.
The effect of task and training on intermediate representations in convolutional neural networks revealed with modified RV similarity analysis
Visualizing structure and transitions in high-dimensional biological data.
Detecting GAN generated errors.
Applying Knowledge Transfer for Water Body Segmentation in Peru.
Author correction: Why rankings of biomedical image analysis competitions should be interpreted with care (Nature Communications, (2018), 9, 1, (5217), 10.1038/s41467-018-07619-7)
Finding Archetypal Spaces Using Neural Networks
Coupling between human brain activity and body movements: Insights from non-invasive electromagnetic recordings
Expressiveness and Learning of Hidden Quantum Markov Models.
AISTATS 2019
(2019-12-01)
ui.adsabs.harvard.edu[LATEST on arXiv preprint arXiv:1912.02098 (2019-12-02)]Automated curriculum generation for Policy Gradients from Demonstrations.
2019-11
Bisimulation for Feller-Dynkin Processes
Electronic Notes in Theoretical Computer Science
(2019-11-30)
www.sciencedirect.com[Also on arXiv preprint arXiv:1904.00976 (2019-04-01)]Deconstructing and reconstructing word embedding algorithms
Option-critic in cooperative multi-agent systems
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift.
Drivers' Awareness, Knowledge, and Use of Autonomous Driving Assistance Systems (ADAS) and Vehicle Automation
Universality and diversity in human song.
JANOS: An Integrated Predictive and Prescriptive Modeling Framework.
Game theoretical analysis of Kidney Exchange Programs.
Online Learned Continual Compression with Stacked Quantization Module.
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models.
Etalumis: bringing probabilistic programming to scientific simulators at scale
Etalumis: bringing probabilistic programming to scientific simulators at scale
Etalumis: bringing probabilistic programming to scientific simulators at scale
Inductive Relation Prediction on Knowledge Graphs.
Distinct functional roles of the mirror neuron system and the mentalizing system.
Universal Dependencies 2.5
SST'19 - Software and Systems Traceability: Summary of the 10th International Workshop at the 41st International Conference on Software Engineering (ICSE), May 27, 2019
oRNAment: a database of putative RNA binding protein target sites in the transcriptomes of model species.
Nonlinear chance-constrained problems with applications to hydro scheduling
Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms.
Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Text
Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing
(2019-11-13)
dblp.uni-trier.dePDFKEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
Selective Brain Damage: Measuring the Disparate Impact of Model Pruning
What Do Compressed Deep Neural Networks Forget
Myeloarchitecture gradients in the human insula serve as blueprints for its diverse connectivity and function
Connecting First and Second Order Recurrent Networks with Deterministic Finite Automata.
Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security
(2019-11-11)
dblp.uni-trier.de[Also on arXiv preprint arXiv:1906.06784 (2019-06-16)]Preventing Posterior Collapse in Sequence VAEs with Pooling
Robo-PlaNet: Learning to Poke in a Day
Integral formulations of volumetric transmittance
Non-linear sphere tracing for rendering deformed signed distance fields
Study of Constrained Network Structures for WGANs on Numeric Data Generation.
Learning to Fix Build Errors with Graph2Diff Neural Networks.
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
Referring Expression Generation Using Entity Profiles
IJCNLP 2019
(2019-11-03)
www.emnlp-ijcnlp2019.orgPDF[Also on arXiv preprint arXiv:1909.01528 (2019-09-04)]Countering the effects of lead bias in news summarization via multi-stage training and auxiliary losses
IJCNLP 2019
(2019-11-03)
www.emnlp-ijcnlp2019.orgPDF[Also on arXiv preprint arXiv:1909.04028 (2019-09-08)]How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
IJCNLP 2019
(2019-11-03)
www.emnlp-ijcnlp2019.orgPDF[Also on arXiv preprint arXiv:1908.06177 (2019-08-16)]GRLA 2019: The first International Workshop on Graph Representation Learning and its Applications
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
Adversarial target-invariant representation learning for domain generalization
Interactive Language Learning by Question Answering
IJCNLP 2019
(2019-11-03)
www.emnlp-ijcnlp2019.org[Also on arXiv preprint arXiv:1908.10909 (2019-08-28)]Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Text
Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing
(2019-11-01)
www.aclweb.orgPDFRadioLoc: Learning Vehicle Locations with FM Signal in All-Terrain Environments
Cascaded Gaussian Processes for Data-efficient Robot Dynamics Learning
A Reduction from Reinforcement Learning to No-Regret Online Learning
AISTATS 2019
(2019-11-01)
proceedings.mlr.press[LATEST on arXiv preprint arXiv:1911.05873 (2019-11-14)]Option-critic in cooperative multi-agent systems
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning
AISTATS 2019
(2019-11-01)
proceedings.mlr.press[LATEST on arXiv preprint arXiv:1911.05010 (2019-11-12)]Deep Generative Modeling of LiDAR Data
2019-10
Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments
Attention for Inference Compilation.
Deep Probabilistic Surrogate Networks for Universal Simulator Approximation.
Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales.
gradSLAM: Dense SLAM meets Automatic Differentiation.
Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery.
Amortized Rejection Sampling in Universal Probabilistic Programming.
Predicting ice flow using machine learning.
Toward Metrics for Differentiating Out-of-Distribution Sets
Toward Metrics for Differentiating Out-of-Distribution Sets.
A language processing algorithm for predicting tactical solutions to an operational planning problem under uncertainty.
Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference
Saliency Based Deep Neural Network for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI
Efficient Inference Amortization in Graphical Models using Structured Continuous Conditional Normalizing Flows
Learning chordal extensions.
SGP: Spotting Groups Polluting the Online Political Discourse.
Visual short‐term memory activation patterns in adult survivors of childhood acute lymphoblastic leukemia
Connections between Support Vector Machines, Wasserstein distance and gradient-penalty GANs
Deep learning for Aerosol Forecasting
Nash Games Among Stackelberg Leaders.
When Nash Meets Stackelberg
Actor Critic with Differentially Private Critic.
Improving Pathological Structure Segmentation via Transfer Learning Across Diseases
Early Prediction of Alzheimer's Disease Progression Using Variational Autoencoders.
InfoMask: Masked Variational Latent Representation to Localize Chest Disease
Visualizing High Dimensional Dynamical Processes
PAC-Bayesian Contrastive Unsupervised Representation Learning
PAC-Bayesian Contrastive Unsupervised Representation Learning
BIAS: Transparent reporting of biomedical image analysis challenges
MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions.
Exploring single-cell data with deep multitasking neural networks.
Benchmarking Batch Deep Reinforcement Learning Algorithms.
NeuroPycon: A free Python toolbox for fast multi-modal and reproducible brain connectivity pipelines
Efficient Graph Generation with Graph Recurrent Attention Networks
A deep learning framework for neuroscience.
Singular value automata and approximate minimization
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
Deep Parametric Indoor Lighting Estimation
ICCV 2019
(2019-10-01)
openaccess.thecvf.comPDF[LATEST on arXiv preprint arXiv:1910.08812 (2019-10-19)]Metal-organic frameworks based fluorescent sensor array for discrimination of flavonoids.
Learning chordal extensions
Decoding the neural dynamics of oculomotor decision making in humans
Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines
Augmenting learning using symmetry in a biologically-inspired domain
Continual Learning of New Sound Classes Using Generative Replay
Improved Conditional VRNNs for Video Prediction
Batch Weight for Domain Adaptation With Mass Shift
Depth with nonlinearity creates no bad local minima in ResNets.
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization
2019-09
Towards modular and programmable architecture search
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
Empowering Graph Representation Learning with Paired Training and Graph Co-Attention
MODELLING BIOLOGICAL ASSAYS WITH ADAPTIVE DEEP KERNEL LEARNING
Unsupervised Temperature Scaling: Robust Post-processing Calibration for Domain Shift
Connectivity-constrained interactive annotations for panoptic segmentation
Beyond GANs: Transforming without a Target Distribution
Fast Training of Sparse Graph Neural Networks on Dense Hardware
Adversarial Privacy Preservation under Attribute Inference Attack
Equivariant Entity-Relationship Networks
Variational inference of latent hierarchical dynamical systems in neuroscience: an application to calcium imaging data
Meta-Graph: Few shot Link Prediction via Meta Learning
Value-driven Hindsight Modelling.
Assessing Generalization in TD methods for Deep Reinforcement Learning
Novelty Search in representational space for sample efficient exploration
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning
Plan2Vec: Unsupervised Representation Learning by Latent Plans
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
Transfer Active Learning For Graph Neural Networks
Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks
Mem2Mem: Learning to Summarize Long Texts with Memory-to-Memory Transfer
Retrieving Signals in the Frequency Domain with Deep Complex Extractors
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
Towards Understanding Generalization in Gradient-Based Meta-Learning
Are Few-shot Learning Benchmarks Too Simple ?
Selfish Emergent Communication
SPECTRA: Sparse Entity-centric Transitions
{COMPANYNAME}11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery
HighRes-net: Multi-Frame Super-Resolution by Recursive Fusion
Equilibrium Propagation with Continual Weight Updates
Underwhelming Generalization Improvements From Controlling Feature Attribution
Learning Neural Causal Models from Unknown Interventions.
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning
Recurrent Independent Mechanisms.
Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures
Avoidance Learning Using Observational Reinforcement Learning
Safer End-to-End Autonomous Driving via Conditional Imitation Learning and Command Augmentation
Discovery of high-confidence human protein-coding genes and exons by whole-genome PhyloCSF helps elucidate 118 GWAS loci.
Revisit Policy Optimization in Matrix Form.
Learning Sparse Mixture of Experts for Visual Question Answering
Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters
Kotlin∇: A shape-safe DSL for differentiable programming
I-MAD: A Novel Interpretable Malware Detector Using Hierarchical Transformer.
Learning Speaker Representations with Mutual Information.
INTERSPEECH 2019
(2019-09-15)
dblp.uni-trier.dePDF[Also on arXiv preprint arXiv:1812.00271 (2018-12-01)]Speech Model Pre-training for End-to-End Spoken Language Understanding
INTERSPEECH 2019
(2019-09-15)
ui.adsabs.harvard.eduPDF[Also on arXiv preprint arXiv:1904.03670 (2019-04-07)]Retrieving Signals with Deep Complex Extractors
Neural Architecture Search for Class-incremental Learning.
Torchmeta: A Meta-Learning library for PyTorch
Recurrent neural networks learn robust representations by dynamically balancing compression and expansion
The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging.
Modelling Working Memory using Deep Recurrent Reinforcement Learning
Recurrent neural networks learn robust representations by dynamically balancing compression and expansion
Inferring hierarchies of latent features in calcium imaging data
Finite Approximation of LMPs for Exact Verification of Reachability Properties.
Fairness and discrimination in recommendation and retrieval
Geometric wavelet scattering on graphs and manifolds
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
Quantifying the effect of experimental perturbations in single-cell RNA-sequencing data using graph signal processing
No Press Diplomacy: Modeling Multi-Agent Gameplay
Deep learning for brains?: Different linear and nonlinear scaling in UK Biobank brain images vs. machine-learning datasets
Teaching Modelling Literacy: An Artificial Intelligence Approach
Learning of Image Dehazing Models for Segmentation Tasks
Toward Requirements Specification for Machine-Learned Components
2019 IEEE 27th International Requirements Engineering Conference Workshops (REW)
(2019-09-01)
dblp.uni-trier.deScattering Networks for Hybrid Representation Learning
2019-08
Digital Democracy Project: Research memo #2 - climate change
Distinction Maximization Loss: Fast, Scalable, Turnkey, and Native Neural Networks Out-of-Distribution Detection simply by Replacing the SoftMax Loss.
Isotropic Maximization Loss and Entropic Score: Fast, Accurate, Scalable, Unexposed, Turnkey, and Native Neural Networks Out-of-Distribution Detection
Online Continual Learning with Maximally Interfered Retrieval.
Medical concept embedding with multiple ontological representations
Digital Democracy Project: Research memo #1 - Media, knowledge and misinformation
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment
An end-to-end neighborhood-based interaction model for knowledge-enhanced recommendation
Proceedings of the 1st International Workshop on Deep Learning Practice for High-Dimensional Sparse Data
(2019-08-05)
ui.adsabs.harvard.edu[LATEST on arXiv preprint arXiv:1908.04032 (2019-08-12)]A thousand studies for the price of one: Accelerating psychological science with Pushkin.
Leaking your engine speed by spectrum analysis of real-Time scheduling sequences
Deep Active Localization
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents.
Expressiveness of probabilistic modal logics: A gradual approach
Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks.
Interpolation Consistency Training for Semi-supervised Learning
2019-07
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation.
Morphological Irregularity Correlates with Frequency
Towards Lossless Encoding of Sentences
A Cross-Domain Transferable Neural Coherence Model
The KnowRef Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution
EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
On the impressive performance of randomly weighted encoders in summarization tasks
Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study
Subspace neural physics: fast data-driven interactive simulation
Hierarchical Gating Networks for Sequential Recommendation
ER-AE: Differentially-private Text Generation for Authorship Anonymization
DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
Session details: Session 3A: Recommendations 1
Fairness and Discrimination in Retrieval and Recommendation
DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
Improved Knowledge Graph Embedding Using Background Taxonomic Information.
Learning Options with Interest Functions
Noisy Interactive Quantum Communication
Prediction of mRNA subcellular localization using deep recurrent neural networks.
Large-scale mammalian genome rearrangements coincide with chromatin interactions.
Predictive learning extracts latent space representations from sensory observations
Hyperparameter optimization in black-box image processing using differentiable proxies
Learning to Handle Parameter Perturbations in Combinatorial Optimization: an Application to Facility Location.
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Incorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks
B-IoT: Blockchain Driven Internet of Things with Credit-Based Consensus Mechanism
Smoother: A Smooth Renewable Power-Aware Middleware
Weakly-supervised Knowledge Graph Alignment with Adversarial Learning
Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning
Learning the Arrow of Time
Scalable Virtual Ray Lights Rendering for Participating Media
2019-06
RADICL-seq identifies general and cell type-specific principles of genome-wide RNA-chromatin interactions
Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments
Learning Causal State Representations of Partially Observable Environments
Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia
Adversarial Computation of Optimal Transport Maps
Investigating Biases in Textual Entailment Datasets.
A Cross-National Study of Consumer Behaviour, Innovativeness and Apparel
Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning
Auto-Encoders, Distributed Training and Information Representation in Deep Neural Networks
Applications of complex numbers to deep neural networks
Agnostic data debiasing through a local sanitizer learnt from an adversarial network approach.
Adversarial Task-Specific Privacy Preservation under Attribute Attack.
Inherent Tradeoffs in Learning Fair Representations
GEAR: Geometry-Aware Rényi Information.
GAIT: A Geometric Approach to Information Theory
On the interplay between noise and curvature and its effect on optimization and generalization
Information matrices and generalization
Heterogeneous Robot Teams for Informative Sampling.
Lower Bounds and Conditioning of Differentiable Games.
Anomaly Detection with Joint Representation Learning of Content and Connection
Conditional Computation for Continual Learning
Reinforcement Learning with Non-uniform State Representations for Adaptive Search
Volume Path Guiding Based on Zero-Variance Random Walk Theory
Distinct roles of parvalbumin and somatostatin interneurons in the synchronization of spike-times in the neocortex
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces.
Neocortical inhibitory interneuron subtypes display distinct responses to synchrony and rate of inputs
Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training.
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Games
A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games.
Learning to evoke complex motor outputs with spatiotemporal neurostimulation using a hierarchical and adaptive optimization algorithm
Learning Powerful Policies by Using Consistent Dynamics Model.
Tackling Climate Change with Machine Learning
Understanding the Impact of Entropy on Policy Optimization
Stochastic Gradient Push for Distributed Deep Learning
Amortized Monte Carlo Integration
ICML 2019
(2019-06-09)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:1907.08082 (2019-07-18)]GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
Off-Policy Deep Reinforcement Learning without Exploration
Fairwashing: the risk of rationalization
The Value Function Polytope in Reinforcement Learning
Statistics and Samples in Distributional Reinforcement Learning
DeepMDP: Learning Continuous Latent Space Models with Theoretical Guarantees
On Learning Invariant Representation for Domain Adaptation
Compositional Invariance Constraints for Graph Embeddings
Per-Decision Option Discounting
Separable value functions across time-scales
TarMAC: Targeted Multi-Agent Communication
Multi-objective training of Generative Adversarial Networks with multiple discriminators
Unreproducible research is reproducible
Note on the bias and variance of variational inference.
Hierarchical Importance Weighted Autoencoders
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
GMNN: Graph Markov Neural Networks
Manifold Mixup: Better Representations by Interpolating Hidden States
On the Spectral Bias of Neural Networks
Reducing the variance in online optimization by transporting past gradients
Dissociating memory accessibility and precision in forgetting [Collection]
Using Cost-Based Solution Densities from TSP Relaxations to Solve Routing Problems
Learning MILP Resolution Outcomes Before Reaching Time-Limit
GreenBroker: Optimal Electric Vehicle Park-and-Charge Control via Vehicle-to-Infrastructure Communication
Structural Robustness for Deep Learning Architectures
Learning Domain Randomization Distributions for Training Robust Locomotion Policies
Learning Domain Randomization Distributions for Transfer of Locomotion Policies.
Dimensionality compression and expansion in Deep Neural Networks
Understanding the Behaviour of Neural Abstractive Summarizers Using Contrastive Examples
Introducing Graph Smoothness Loss for Training Deep Learning Architectures
Structural Robustness for Deep Learning Architectures
Improved Bounds for Max Consensus in Wireless Networks
A Frequency Analysis and Dual Hierarchy for Efficient Rendering of Subsurface Scattering
Tulip: An open-source interior-point linear optimization solver with abstract linear algebra
QPLIB: a library of quadratic programming instances
An empirical study on aggregation of alternatives and its influence on prediction in car type choice models
2019-05
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
Adverse Event Prediction by Telemonitoring and Deep Learning
Investigating Trust Factors in Human-Robot Shared Control: Implicit Gender Bias Around Robot Voice
Revision in Continuous Space: Fine-Grained Control of Text Style Transfer.
Incremental Mining of High Utility Patterns in One Phase by Absence and Legacy-Based Pruning
Unsupervised Controllable Text Generation with Global Variation Discovery and Disentanglement.
Activity-based analysis of open source software contributors: roles and dynamics
Singular value automata and approximate minimization
Attention Based Pruning for Shift Networks
Bit-Slicing FPGA Accelerator for Quantized Neural Networks
Generalizable Adversarial Attacks Using Generative Models.
Generalizable Adversarial Attacks with Latent Variable Perturbation Modelling
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
Analysis and detection of information types of open source software issue discussions
Stroke Lesion Segmentation in FLAIR MRI Datasets Using Customized Markov Random Fields.
DeepMDP: Learning Continuous Latent Space Models for Representation Learning
ICML 2019
(2019-05-24)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:1906.02736 (2019-06-06)]Compositional Fairness Constraints for Graph Embeddings
ICML 2019
(2019-05-24)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:1905.10674 (2019-05-25)]Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data
Recurrent Value Functions.
The Journey is the Reward: Unsupervised Learning of Influential Trajectories.
Fast non-uniform radiance probe placement and tracing
Asm2Vec: Boosting Static Representation Robustness for Binary Clone Search against Code Obfuscation and Compiler Optimization
Underwater Communication Using Full-Body Gestures and Optimal Variable-Length Prefix Codes
In Support of Over-Parametrization in Deep Reinforcement Learning: an Empirical Study
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
Provably Accelerated Randomized Gossip Algorithms
How Transferable Are Features in Convolutional Neural Network Acoustic Models across Languages
Representation Mixing for TTS Synthesis
The Pytorch-kaldi Speech Recognition Toolkit
ICASSP 2019
(2019-05-12)
hal.archives-ouvertes.frPDF[Also on arXiv preprint arXiv:1811.07453 (2018-11-19)]Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction
Deep Generative and Discriminative Domain Adaptation
Building Knowledge for AI Agents with Reinforcement Learning
On the Pitfalls of Measuring Emergent Communication
Learning Graphs From Data: A Signal Representation Perspective
Learning Graphs From Data: A Signal Representation Perspective
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
Representation Learning on Graphs and Manifolds
Task-Agnostic Reinforcement Learning (TARL)
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
A Variational Inequality Perspective on Generative Adversarial Networks
Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Systematic Generalization: What Is Required and Can It Be Learned?
Reproducibility in Machine Learning
AI for Social Good
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Adversarial Domain Adaptation for Stable Brain-Machine Interfaces
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Deep Graph Infomax
Learning deep representations by mutual information estimation and maximization
On overfitting and asymptotic bias in batch reinforcement learning with partial observability
Usability of Virtual Reality Application Through the Lens of the User Community: A Case Study
Drug-Drug Adverse Effect Prediction with Graph Co-Attention
Usability of Virtual Reality Application Through the Lens of the User Community: A Case Study
Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks
Structure Learning for Neural Module Networks.
A Survey on Gradient-Domain Rendering
Semantic Mapping for View-Invariant Relocalization
Generating Adversarial Driving Scenarios in High-Fidelity Simulators
Prediction of Progression to Alzheimer's disease with Deep InfoMax
Moving beyond reward prediction errors
Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks
Introducing Graph Smoothness Loss for Training Deep Learning Architectures
A Highly Adaptive Acoustic Model for Accurate Multi-dialect Speech Recognition
A Data-Efficient Framework for Training and Sim-to-Real Transfer of Navigation Policies
2019-04
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks.
Faster and More Accurate Trace-based Policy Evaluation via Overall Target Error Meta-Optimization
META-Learning State-based {\lambda} for More Sample-Efficient Policy Evaluation
A deep neural network approach to investigate tone space in languages
Compositional generalization in a deep seq2seq model by separating syntax and semantics.
Human Motion Prediction Via Pattern Completion in Latent Representation Space
Solving Quadratic Programming by Cutting Planes
GradMask: Reduce Overfitting by Regularizing Saliency.
International Conference on Medical Imaging with Deep Learning -- Extended Abstract Track
(2019-04-16)
dblp.uni-trier.dePDF[Also on arXiv preprint arXiv:1904.07478 (2019-04-16)]An Algorithm for Assortment Optimization Under Parametric Discrete Choice Models
Spatio-Temporal Deep Graph Infomax.
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models
AISTATS 2019
(2019-04-11)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1903.02482 (2019-03-06)]Distributional reinforcement learning with linear function approximation
AISTATS 2019
(2019-04-11)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1902.03149 (2019-02-08)]The Termination Critic
AISTATS 2019
(2019-04-11)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1902.09996 (2019-02-26)]Multitask Metric Learning: Theory and Algorithm
Negative Momentum for Improved Game Dynamics
Active Domain Randomization.
Reinforced Imitation in Heterogeneous Action Space.
Learning Problem-Agnostic Speech Representations from Multiple Self-Supervised Tasks.
Flight-connection prediction for airline crew scheduling to construct initial clusters for OR optimizer
Distributed Data Center Bandwidth Allocation for Cloud-Based Streaming
Rapid Genetic Code Evolution in Green Algal Mitochondrial Genomes
2019-03
An Introduction to Deep Reinforcement Learning
MLSys: The New Frontier of Machine Learning Systems
InfoMask: Masked Variational Latent Representation to Localize Chest Disease
A RAD approach to deep mixture models
Dataflow-Based Joint Quantization for Deep Neural Networks
Reconfigurable Battery Systems: A Survey on Hardware Architecture and Research Challenges
Towards Standardization of Data Licenses: The Montreal Data License
Online continual learning with no task boundaries.
Learning proposals for sequential importance samplers using reinforced variational inference.
Gated Orthogonal Recurrent Units: On Learning to Forget
Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases
Imitation Learning of Factored Multi-agent Reactive Models
Adversarial Mixup Resynthesizers
On Adversarial Mixup Resynthesis
Towards Secure Industrial IoT: Blockchain System With Credit-Based Consensus Mechanism
Deep Active Localization.
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future.
Ten years of feasibility pump, and counting
Improving NILM by Combining Sensor Data and Linear Programming
Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction.
AMIA 2019
(2019-03-01)
ui.adsabs.harvard.eduPDF[LATEST on arXiv preprint arXiv:1903.08652 (2019-03-20)]2019-02
2C-ChIP: measuring chromatin immunoprecipitation signal from defined genomic regions with deep sequencing
Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification.
How Do the Open Source Communities Address Usability and UX Issues? An Exploratory Study
When AIs Outperform Doctors: Confronting the Challenges of a Tort-Induced Over-Reliance on Machine Learning
Hyperbolic Discounting and Learning over Multiple Horizons
Adaptive Sampling for Sound Propagation
Anytime Tail Averaging.
Searchable Storage in Cloud Computing
Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition
Negative eigenvalues of the Hessian in deep neural networks.
Separating value functions across time-scales
Multi-Channel Based Sybil Attack Detection in Vehicular Ad Hoc Networks Using RSSI
Dendritic solutions to the credit assignment problem.
The Impact of Time Interval between Extubation and Reintubation on Death or Bronchopulmonary Dysplasia in Extremely Preterm Infants.
2019-01
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
Shaping the Narrative Arc: An Information-Theoretic Approach to Collaborative Dialogue.
The Value Function Polytope in Reinforcement Learning
A Geometric Perspective on Optimal Representations for Reinforcement Learning
The Second Conversational Intelligence Challenge (ConvAI2)
Why rankings of biomedical image analysis competitions should be interpreted with care (vol 9, 5217, 2018)
Author Correction: Why rankings of biomedical image analysis competitions should be interpreted with care.
Gated Attentive-Autoencoder for Content-Aware Recommendation
Session-Based Social Recommendation via Dynamic Graph Attention Networks
InfoBot: Transfer and Exploration via the Information Bottleneck
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Learning Phenotypes and Dynamic Patient Representations via RNN Regularized Collective Non-negative Tensor Factorization
Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift
A Comparative Analysis of Expected and Distributional Reinforcement Learning
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Generating Character Descriptions for Automatic Summarization of Fiction
Learning Multi-task Communication with Message Passing for Sequence Learning
Leveraging observations in bandits: Between risks and benefits
Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks
On-line Adaptative Curriculum Learning for GANs
Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies
Combined Reinforcement Learning via Abstract Representations
Maximum Entropy Generators for Energy-Based Models.
Towards a Knowledge-Based Recommender System for Linking Electronic Patient Records With Continuing Medical Education Information at the Point of Care
A Hybrid Framework for Sentiment Analysis Using Genetic Algorithm Based Feature Reduction
Equivalence of Equilibrium Propagation and Recurrent Backpropagation.
Neural Computation
(2019-01-18)
ui.adsabs.harvard.eduPDF[Also on 2018 Conference on Cognitive Computational Neuroscience (2018-01-01)]Cross-Domain Noise Impact Evaluation for Black Box Two-Level Control CPS
Development of a ranking procedure for energy performance evaluation of buildings based on occupant behavior
The Liver Tumor Segmentation Benchmark (LiTS)
What comes next? Extractive summarization by next-sentence prediction.
The Benefits of Over-parameterization at Initialization in Deep ReLU Networks
Scalable appearance filtering for complex lighting effects
Wordnet-Based Criminal Networks Mining for Cybercrime Investigation
An Efficient UAV Hijacking Detection Method Using Onboard Inertial Measurement Unit
Cortical network mechanisms of anodal and cathodal transcranial direct current stimulation in awake primates
Arabic Authorship Attribution: An Extensive Study on Twitter Posts
The AI Driving Olympics: An Accessible Robot Learning Benchmark
Impulse Responses for Precomputing Light from Volumetric Media.
Graph-Based Compression for Distributed Particle Filters
Uncertainty Principle on Graphs
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow.
View-dependent Radiance Caching.
Learning Stylometric Representations for Authorship Analysis
Evaluating systematicity in neural networks with natural language inference.
On Robustness: An Undervalued Dimension of Human Rationality.
Harmonic Syntax in Time: Rhythm Improves Grammatical Models of Harmony.
HyperCo: Optimizing Network Performance in ARM-Based Mobile Virtualization
Indoor Localization Based on Channel State Information
Bandwidth and Energy Efficient Image Sharing for Situation Awareness in Disasters
Traceability in the Wild: Automatically Augmenting Incomplete Trace Links.
Bioinformatics Approaches to Gain Insights into cis-Regulatory Motifs Involved in mRNA Localization.
A Decentralized Framework for the Optimal Coordination of Distributed Energy Resources
Learning to evoke complex motor outputs with spatiotemporal neurostimulation using a hierarchical and adaptive optimization algorithm.
Community size effect in artificial learning systems.
Learning Reliable Policies in the Bandit Setting with Application to Adaptive Clinical Trials.
Temporally Extended Metrics for Markov Decision Processes.
Learning Modular Safe Policies in the Bandit Setting with Application to Adaptive Clinical Trials.
Seeded self-play for language learning.
Leveraging exploration in off-policy algorithms via normalizing flows.
Attending Over Triads for Learning Signed Network Embedding
Probability Distillation: A Caveat and Alternatives.
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering.
Stochastic Neural Network with Kronecker Flow.
AISTATS 2019
(2019-01-01)
dblp.uni-trier.dePDF[LATEST on arXiv preprint arXiv:1906.04282 (2019-06-10)]InfoBot: Structured Exploration in ReinforcementLearning Using Information Bottleneck
2018-12
Regularized Binary Network Training
Ethical Challenges in Data-Driven Dialogue Systems
Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks.
Double-Stranded Biotinylated Donor Enhances Homology-Directed Repair in Combination with Cas9 Monoavidin in Mammalian Cells.
An Introduction to Deep Reinforcement Learning
Clustering-Oriented Representation Learning with Attractive-Repulsive Loss.
Prediction of Progression in Multiple Sclerosis Patients
International Conference on Medical Imaging with Deep Learning -- Full Paper Track
(2018-12-13)
openreview.netPDFSpeech and Speaker Recognition from Raw Waveform with SincNet
Effectiveness of Alter Sampling in Social Networks.
Why rankings of biomedical image analysis competitions should be interpreted with care
The effects of negative adaptation in Model-Agnostic Meta-Learning
Recurrent transition networks for character locomotion
Learning safe policies with expert guidance
Automatic differentiation in ML: Where we are and where we should be going
Faithful Inversion of Generative Models for Effective Amortized Inference
Bayesian Distributed Stochastic Gradient Descent
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation
Dual Policy Iteration
Learning Beam Search Policies via Imitation Learning
Adversarial Multiple Source Domain Adaptation
Embedding Logical Queries on Knowledge Graphs
Hierarchical Graph Representation Learning with Differentiable Pooling
Temporal Regularization for Markov Decision Process
Unsupervised Depth Estimation, 3D Face Rotation and Replacement
Towards Deep Conversational Recommendations
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates
Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis
Improving Explorability in Variational Inference with Annealed Variational Objectives
Towards Text Generation with Adversarially Learned Neural Outlines
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding
Bayesian Model-Agnostic Meta-Learning
MetaGAN: An Adversarial Approach to Few-Shot Learning
Dendritic cortical microcircuits approximate the backpropagation algorithm
Image-to-image translation for cross-domain disentanglement
Scheduling M2M traffic over LTE uplink of a dense small cell network
Eurasip Journal on Wireless Communications and Networking
(2018-12-01)
jwcn-eurasipjournals.springeropen.comPDFDeep Learning recognizes weather and climate patterns
Deep convolutional networks for quality assessment of protein folds.
2018-11
Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis
A Graph-CNN for 3D Point Cloud Classification
Understanding the impact of entropy in policy learning
Multi-task Learning over Graph Structures.
Environments for Lifelong Reinforcement Learning.
A Survey of Mobile Computing for the Visually Impaired.
Autonomous Marine Sampling Enhanced by Strategically Deployed Drifters in Marine Flow Fields
Planning in Dynamic Environments with Conditional Autoregressive Models.
Keep Drawing It: Iterative language-based image generation and editing.
Interpretable Convolutional Filters with SincNet
A natural history of song [working paper]
Contextualized Non-local Neural Networks for Sequence Learning
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
Harmonic Recomposition using Conditional Autoregressive Modeling.
Signatures and mechanisms of low-dimensional neural predictive manifolds
The Barbados 2018 List of Open Issues in Continual Learning.
On Training Recurrent Neural Networks for Lifelong Learning
An Introduction to Probabilistic Programming.
Verification of Recurrent Neural Networks Through Rule Extraction.
Natural Environment Benchmarks for Reinforcement Learning.
Blindfold Baselines for Embodied QA.
Compositional Language Understanding with Text-based Relational Reasoning.
The RLLChatbot: a solution to the ConvAI challenge.
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Navigation in the Service of Enhanced Pose Estimation
Policy Search on Aggregated State Space for Active Sampling
On the Evaluation of Common-Sense Reasoning in Natural Language Understanding.
Defending Against Adversarial Samples Without Security through Obscurity
Temporal Regularization in Markov Decision Process
2018-10
A Knowledge Hunting Framework for Common Sense Reasoning
A Hierarchical Neural Attention-based Text Classifier
BanditSum: Extractive Summarization as a Contextual Bandit
Extending Neural Generative Conversational Model using External Knowledge Sources
Auto-Encoding Dictionary Definitions into Consistent Word Embeddings
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Sim-to-Real Transfer with Neural-Augmented Robot Simulation
BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop.
Deep Learning. Das umfassende Handbuch
h-detach: Modifying the LSTM Gradient Towards Better Optimization.
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods.
Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio
A Knowledge Hunting Framework for Common Sense Reasoning
Computing Nash equilibria for integer programming games
Recurrent semi-supervised classification and constrained adversarial generation with motion capture data
2018-09
EnGAN: Latent Space MCMC and Maximum Entropy Generators for Energy-based Models
On Difficulties of Probability Distillation
RNNs with Private and Shared Representations for Semi-Supervised Sequence Learning
Hiding Objects from Detectors: Exploring Transferrable Adversarial Patterns
BNN+: Improved Binary Network Training
Revisiting Reweighted Wake-Sleep
Where Off-Policy Deep Reinforcement Learning Fails
Shaping representations through communication
Learning powerful policies and better dynamics models by encouraging consistency
Data Poisoning Attack against Unsupervised Node Embedding Methods
Visualizing and Discovering Behavioural Weaknesses in Deep Reinforcement Learning
Visual Imitation Learning with Recurrent Siamese Networks.
A Modern Take on the Bias-Variance Tradeoff in Neural Networks
W2GAN: RECOVERING AN OPTIMAL TRANSPORT MAP WITH A GAN
Pix2Scene: Learning Implicit 3D Representations from Images
Towards the Latent Transcriptome
Unsupervised one-to-many image translation
Convergence Properties of Deep Neural Networks on Separable Data
DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation
Universal Successor Features for Transfer Reinforcement Learning
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations
Manifold Mixup: Learning Better Representations by Interpolating Hidden States
How can deep learning advance computational modeling of sensory information processing
On the Learning Dynamics of Deep Neural Networks.
Machine Learning to Predict Osteoporotic Fracture Risk from Genotypes
Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding
Social-Affiliation Networks: Patterns and the SOAR Model
Visual Reasoning with Multi-hop Feature Modulation
Safe Nonlinear Trajectory Generation for Parallel Autonomy With a Dynamic Vehicle Model
Learning from Narrated Instruction Videos
IEEE Transactions on Pattern Analysis and Machine Intelligence
(2018-09-01)
hal.archives-ouvertes.frPDF2018-08
Approximate Exploration through State Abstraction.
A Semi-Markov Chain Approach to Modeling Respiratory Patterns Prior to Extubation in Preterm Infants.
Predicting Extubation Readiness in Extreme Preterm Infants based on Patterns of Breathing
Undersampling and Bagging of Decision Trees in the Analysis of Cardiorespiratory Behavior for the Prediction of Extubation Readiness in Extremely Preterm Infants.
Generalization of Equilibrium Propagation to Vector Field Dynamics.
Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields
A PCA-based approximation scheme for combinatorial optimization with uncertain and correlated data
2018-07
Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information
Predicting Solution Summaries to Integer Linear Programs under Imperfect Information with Machine Learning.
Speaker Recognition from Raw Waveform with SincNet
Attend Before you Act: Leveraging human visual attention for continual learning.
Safe Option-Critic: Learning Safety in the Option-Critic Architecture
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Active Search of Connections for Case Building and Combating Human Trafficking
Let's do it ``again'': A First Computational Approach to Detecting Adverbial Presupposition Triggers
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
DNN's Sharpest Directions Along the SGD Trajectory.
Negative Momentum for Improved Game Dynamics.
The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach.
On Nesting Monte Carlo Estimators
Deep Variational Reinforcement Learning for POMDPs
Tighter Variational Bounds are Not Necessarily Better
Convergent Tree-Backup and Retrace with Function Approximation
Neural Autoregressive Flows
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Focused Hierarchical RNNs for Conditional Sequence Processing
Mutual Information Neural Estimator
Leveraging Observational Learning for Exploration in Bandits
Eligibility Traces for Options
Feature-wise transformations
MaD TwinNet: Masker-Denoiser Architecture with Twin Networks for Monaural Sound Source Separation
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning
AISTATS 2018
(2018-07-04)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1807.01406 (2018-07-04)]Undersampling and Bagging of Decision Trees in the Analysis of Cardiorespiratory Behavior for the Prediction of Extubation Readiness in Extremely Preterm Infants
2018-06
A Comparison of Optimization Methods for Multi-objective Constrained Bin Packing Problems
Learning a classification of mixed-integer quadratic programming problems
Inference Trees: Adaptive Inference with Exploration
On the Spectral Bias of Deep Neural Networks
Local Positioning System Using UWB Range Measurements for an Unmanned Blimp
Fashion-Gen: The Generative Fashion Dataset and Challenge
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning
Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition.
INTERSPEECH 2018
(2018-06-20)
dblp.uni-trier.dePDF[Also on arXiv preprint arXiv:1806.07789 (2018-06-20)]Learning Distributed Representations from Reviews for Collaborative Filtering
Improving Landmark Localization with Semi-Supervised Learning
Modularity Matters: Learning Invariant Relational Reasoning Tasks
Towards Gene Expression Convolutions using Gene Interaction Graphs
Diffusion-Based Approximate Value Functions
Manifold Mixup: Better Representations by Interpolating Hidden States.
Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer.
Quaternion Recurrent Neural Networks
Focused Hierarchical RNNs for Conditional Sequence Processing
Oríon : Experiment Version Control for Efficient Hyperparameter Optimization
RE-EVALUATE: Reproducibility in Evaluating Reinforcement Learning Algorithms
Learning to rank for censored survival data.
A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version
Randomized Value Functions via Multiplicative Normalizing Flows
UAI 2018
(2018-06-01)
ui.adsabs.harvard.eduPDF[LATEST on arXiv preprint arXiv:1806.02315 (2018-06-06)]On the Iterative Refinement of Densely Connected Representation Levels for Semantic Segmentation
2018-05
Dyna Planning using a Feature Based Generative Model.
Learning Steering Bounds for Parallel Autonomous Systems
Autonomous Vehicle Navigation in Rural Environments Without Detailed Prior Maps
Convolutional networks for kidney segmentation in contrast-enhanced CT scans
Computer methods in biomechanics and biomedical engineering. Imaging & visualization
(2018-05-04)
doi.orgGeneralization in Deep Learning
Mathematics of Deep Learning, Cambridge University Press. Prepint avaliable as: MIT-CSAIL-TR-2018-014, Massachusetts Institute of Technology
(2018-05-01)
lis.csail.mit.eduPDF2018-04
Low-memory convolutional neural networks through incremental depth-first processing.
Twin Regularization for online speech recognition
INTERSPEECH 2018
(2018-04-15)
dblp.uni-trier.dePDF[Also on arXiv preprint arXiv:1804.05374 (2018-04-15)]Monaural Singing Voice Separation with Skip-Filtering Connections and Recurrent Inference of Time-Frequency Mask
Geometric Consistency for Self-Supervised End-to-End Visual Odometry
Iteratively unveiling new regions of interest in Deep Learning models
Convolutional neural networks for mesh-based parcellation of the cerebral cortex
Discontinuous Hamiltonian Monte Carlo for Probabilistic Programs.
Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities
Fine-grained attention mechanism for neural machine translation
Neurocomputing
(2018-04-05)
www.sciencedirect.com[Also on arXiv preprint arXiv:1803.11407 (2018-03-30)]Neural Autoregressive Flows
Experiments on virtual private network design with concave capacity costs
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Commonsense mining as knowledge base completion? A study on the impact of novelty
Proceedings of the Workshop on Generalization in the Age of Deep Learning
(2018-04-01)
ui.adsabs.harvard.edu[LATEST on arXiv preprint arXiv:1804.09259 (2018-04-24)]Drawing and Recognizing Chinese Characters with Recurrent Neural Network
2018-03
Accelerated Stochastic Power Iteration
Nonlinear Weighted Finite Automata
Frank-Wolfe Splitting via Augmented Lagrangian Method
AISTATS 2018
(2018-03-31)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:1804.03176 (2018-04-09)]Constructing Temporal Abstractions Autonomously in Reinforcement Learning
Learning Anonymized Representations with Adversarial Neural Networks
Light Gated Recurrent Units for Speech Recognition
Generating Contradictory, Neutral, and Entailing Sentences
A polynomial algorithm for a continuous bilevel knapsack problem
2018-02
A Variational Inequality Perspective on Generative Adversarial Nets
Disentangling the independently controllable factors of variation by interacting with the world
A Walk with SGD.
Towards End-to-end Spoken Language Understanding
Generalization in Machine Learning via Analytical Learning Theory
Sequential Coordination of Deep Models for Learning Visual Arithmetic
An inference-based policy gradient method for learning options
YellowFin and the Art of Momentum Tuning
Learning Representations and Generative Models for 3D Point Clouds
SEARNN: Training RNNs with global-local losses
Parametric Adversarial Divergences are Good Task Losses for Generative Modeling
Hierarchical Adversarially Learned Inference
Bayesian Hypernetworks
Neural Language Modeling by Jointly Learning Syntax and Lexicon
MINE: Mutual Information Neural Estimation
Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks
Extending the Framework of Equilibrium Propagation to General Dynamics
Image Segmentation by Iterative Inference from Conditional Score Estimation
Learning Generative Models with Locally Disentangled Latent Factors
Boundary Seeking GANs
Variance Regularizing Adversarial Learning
Combining Model-based and Model-free RL via Multi-step Control Variates
Learning to Compute Word Embeddings On the Fly
Learning Independent Features with Adversarial Nets for Non-linear ICA
Fraternal Dropout
Twin Networks: Matching the Future for Sequence Generation
FigureQA: An Annotated Figure Dataset for Visual Reasoning
Three factors influencing minima in SGD
Residual Connections Encourage Iterative Inference
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
Deep Complex Networks
Graph Attention Networks
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
Decoupling Dynamics and Reward for Transfer Learning.
An Evaluation of Fisher Approximations Beyond Kronecker Factorization
Inferring Identity Factors for Grouped Examples
Graph Priors for Deep Neural Networks
Finding Flatter Minima with SGD
Universal Successor Representations for Transfer Reinforcement Learning
ICLR 2018
(2018-02-12)
ui.adsabs.harvard.eduPDF[LATEST on arXiv preprint arXiv:1804.03758 (2018-04-11)]ChatPainter: Improving Text to Image Generation using Dialogue
Learning with Options that Terminate Off-Policy
When Waiting is not an Option : Learning Options with a Deliberation Cost
Learning Predictive State Representations from Non-uniform Sampling
Learning Robust Options
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning
Deep Reinforcement Learning that Matters
FiLM: Visual Reasoning with a General Conditioning Layer
Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation
2018-01
Patterns of reintubation in extremely preterm infants: a longitudinal cohort study.
Neural Models for Key Phrase Detection and Question Generation
Variational Bi-LSTMs
Machine Learning
(2018-01-23)
www.microsoft.com[LATEST on arXiv preprint arXiv:1711.05717 (2018-02-15)]A Deep Reinforcement Learning Chatbot (Short Version)
A3T: Adversarially Augmented Adversarial Training.
Improved asynchronous parallel optimization analysis for stochastic incremental methods
Navigation for Underwater Vehicles
A convex reformulation and an outer approximation for a class of binary quadratic program
Probabilistic cooperative mobile robot area coverage and its application to autonomous seabed mapping
Coarse Lexical Frame Acquisition at the Syntax-Semantics Interface Using a Latent-Variable PCFG Model.
Constructing a Lexicon of Relational Nouns.
A Generalized Knowledge Hunting Framework for the Winograd Schema Challenge
Imitation Upper Confidence Bound for Bandits on a Graph.
Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization.
Genomic Prediction of Osteoporosis Using 426,000 Individuals from UK Biobank
A Decision-Theoretic Approach for the Collaborative Control of a Smart Wheelchair
Streaming kernel regression with provably adaptive mean, variance, and regularization
Reward Estimation for Variance Reduction in Deep Reinforcement Learning.
Improved asynchronous parallel optimization analysis for stochastic incremental methods
HoME: a Household Multimodal Environment.
BigBrain: 1D convolutional neural networks for automated sementation of cortical layers
2018 Annual Meeting of the Organization of Human Brain Mapping (OHBM)
(2018-01-01)
juser.fz-juelich.deLearning Hierarchical Structures On-The-Fly with a Recurrent-Recursive Model for Sequences.
The First Conversational Intelligence Challenge
Introduction to NIPS 2017 Competition Track
Neural Models for Key Phrase Extraction and Question Generation
Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks
2018 Conference on Cognitive Computational Neuroscience
(2018-01-01)
dblp.uni-trier.dePDF[LATEST on arXiv preprint arXiv:1911.08585 (2019-11-15)]Publications collected and formatted using Paperoni