2022-01
Interpolation consistency training for semi-supervised learning.
Neural Networks
(2022-01-01)
www.sciencedirect.comPDF[Also on arXiv preprint arXiv:1903.03825 (2019-03-09)]2021-12
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
Gradient Starvation: A Learning Proclivity in Neural Networks
Neural Production Systems
The Causal-Neural Connection: Expressiveness, Learnability, and Inference
Discrete-Valued Neural Communication
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
2021-11
Problèmes associés au déploiement des modèles fondés sur l’apprentissage machine en santé.
2021-10
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding
Chunked Autoregressive GAN for Conditional Waveform Synthesis
Compositional Attention: Disentangling Search and Retrieval
Graph Neural Networks with Learnable Structural and Positional Representations.
Dynamic Inference with Neural Interpreters
ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods
Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond.
CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.
2021-09
Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information
Informs Journal on Computing
(2021-09-21)
pubsonline.informs.org[Also on arXiv preprint arXiv:1901.07935 (2018-07-31)]Problems in the deployment of machine-learned models in health care.
Learning Neural Causal Models with Active Interventions
2021-07
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
Combating False Negatives in Adversarial Imitation Learning
How does hemispheric specialization contribute to human-defining cognition?
2021-06
Deep learning for AI
Predicting Unreliable Predictions by Shattering a Neural Network
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures.
A Comparative Study of Learning Outcomes for Online Learning Platforms
Exploration-Driven Representation Learning in Reinforcement Learning
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
SpeechBrain: A General-Purpose Speech Toolkit
CMIM: Cross-Modal Information Maximization For Medical Imaging
2021-05
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models.
Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting
GraphMix: Improved Training of GNNs for Semi-Supervised Learning
Exploring the Wasserstein metric for time-to-event analysis
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
Neural Bayes: A Generic Parameterization Method for Unsupervised Learning
Transformers with Competitive Ensembles of Independent Mechanisms
Conditional Networks
Dependency Structure Discovery from Interventions
Meta Attention Networks: Meta-Learning Attention to Modulate Information Between Recurrent Independent Mechanisms
Spatially Structured Recurrent Modules
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments
Predicting Infectiousness for Proactive Contact Tracing
Systematic generalisation with group invariant predictions
Saliency is a Possible Red Herring When Diagnosing Poor Generalization
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
Learning Neural Generative Dynamics for Molecular Conformation Generation
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
Recurrent Independent Mechanisms
2021-04
hBert + BiasCorp - Fighting Racism on the Web
Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion
(2021-04-19)
tspace.library.utoronto.caPDF[Also on arXiv preprint arXiv:2104.02242 (2021-04-06)]Machine learning for combinatorial optimization: A methodological tour d’horizon
European Journal of Operational Research
(2021-04-16)
www.sciencedirect.comPDF[Also on arXiv preprint arXiv:1811.06128 (2018-11-15)]2021-03
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
AISTATS 2021
(2021-03-18)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:2010.08012 (2020-10-15)]A Two-Stream Continual Learning System With Variational Domain-Agnostic Feature Replay.
Coordination Among Neural Modules Through a Shared Global Workspace.
2021-02
Toward Causal Representation Learning
Towards Causal Representation Learning
DEUP: Direct Epistemic Uncertainty Prediction
Structured Sparsity Inducing Adaptive Optimizers for Deep Learning
2021-01
Training neural networks to recognize speech increased their correspondence to the human auditory pathway but did not yield a shared hierarchy of acoustic features
Learning from unexpected events in the neocortical microcircuit
Inherent privacy limitations of decentralized contact tracing apps.
Attention Based Pruning for Shift Networks
ICPR 2021
(2021-01-10)
hal.archives-ouvertes.frPDF[Also on arXiv preprint arXiv:1905.12300 (2019-05-29)]Discrete-Valued Neural Communication in Structured Architectures Enhances Generalization
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing Its Gradient Estimator Bias.
Using Artificial Intelligence to Visualize the Impacts of Climate Change
FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters
Fast And Slow Learning Of Recurrent Independent Mechanisms
2020-12
Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya.
Establishing an evaluation metric to quantify climate change image realism
Informatica : Journal of Applied Machines Electrical Electronics Computer Science and Communication Systems
(2020-12-01)
digitalintelligentsiaconsultancyservices.com[Also on Machine Learning: Science and Technology (2020-04-09)][Also on arXiv preprint arXiv:1910.10143 (2019-10-22)]2020-11
Inductive Biases for Deep Learning of Higher-Level Cognition
Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies
RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design.
Gradient Starvation: A Learning Proclivity in Neural Networks
2020-10
COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing.
The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach
Journal of Artificial Intelligence Research
(2020-10-27)
dblp.uni-trier.dePDF[Also on arXiv preprint arXiv:1807.04723 (2018-07-12)]Predicting Infectiousness for Proactive Contact Tracing
Generative adversarial networks
NU-GAN: High resolution neural upsampling with GAN.
Cross-Modal Information Maximization for Medical Imaging: CMIM.
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
2020-09
Generating Multiscale Amorphous Molecular Structures Using Deep Learning: A Study in 2D
A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs
2020-08
Visual Concept Reasoning Networks
Mastering Rate based Curriculum Learning.
2020-07
Deriving Differential Target Propagation from Iterating Approximate Inverses
Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning
BabyAI 1.1.
S2RMs: Spatially Structured Recurrent Modules.
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
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition.
Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach
Compositional Generalization by Factorizing Alignment and Translation
The need for privacy with public digital contact tracing during the COVID-19 pandemic
2020-06
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems
Hybrid Models for Learning to Branch
Rethinking Distributional Matching Based Domain Adaptation.
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer
Untangling tradeoffs between recurrence and self-attention in neural networks
Learning Causal Models Online.
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias
Codon arrangement modulates MHC-I peptides presentation
On the interplay between noise and curvature and its effect on optimization and generalization
Training End-to-End Analog Neural Networks with Equilibrium Propagation.
HNHN: Hypergraph Networks With Hyperedge Neurons
Multi-Image Super-Resolution for Remote Sensing Using Deep Recurrent Networks
2020-05
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning
An Analysis of the Adaptation Speed of Causal Models
An Analysis of the Adaptation Speed of Causal Models
COVI White Paper.
2020-04
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
Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation.
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning
Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
Experience Grounds Language
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
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.
2020-03
Object-Centric Image Generation from Layouts
On the Morality of Artificial Intelligence [Commentary]
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
Continuous Domain Adaptation with Variational Domain-Agnostic Feature Replay
Benchmarking Graph Neural Networks
2020-02
Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery
Modeling Cloud Reflectance Fields using Conditional Generative Adversarial Networks
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization.
Meta-learning framework with applications to zero-shot time-series forecasting
2020-01
Using Simulated Data to Generate Images of Climate Change
Multi-Task Self-Supervised Learning for Robust Speech Recognition
Hybrid Models for Learning to Branch
Untangling tradeoffs between recurrence and self-attention in artificial neural networks
On Catastrophic Interference in Atari 2600 Games
Toward Training Recurrent Neural Networks for Lifelong Learning.
2019-12
Learning from Learning Machines: Optimisation, Rules, and Social Norms
On the Morality of Artificial Intelligence.
Joint Learning of Generative Translator and Classifier for Visually Similar Classes
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)]How to Initialize your Network? Robust Initialization for WeightNorm & ResNets
Variational Temporal Abstraction
The effect of task and training on intermediate representations in convolutional neural networks revealed with modified RV similarity analysis
Applying Knowledge Transfer for Water Body Segmentation in Peru.
Automated curriculum generation for Policy Gradients from Demonstrations
Unsupervised State Representation Learning in Atari
2019-11
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models.
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)]2019-10
A deep learning framework for neuroscience
Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery.
Predicting ice flow using machine learning.
InfoMask: Masked Variational Latent Representation to Localize Chest Disease
Depth with nonlinearity creates no bad local minima in ResNets.
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization
2019-09
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
Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures
Avoidance Learning Using Observational Reinforcement Learning
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
Torchmeta: A Meta-Learning library for PyTorch
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
2019-08
Interactive Language Learning by Question Answering
2019-07
Combined Reinforcement Learning via Abstract Representations
Weakly-supervised Knowledge Graph Alignment with Adversarial Learning
Learning the Arrow of Time
Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study
2019-06
On the interplay between noise and curvature and its effect on optimization and generalization
Information matrices and generalization
Conditional Computation for Continual Learning
Learning Powerful Policies by Using Consistent Dynamics Model.
Tackling Climate Change with Machine Learning
2019-05
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
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
The Journey is the Reward: Unsupervised Learning of Influential Trajectories.
A Data-Efficient Framework for Training and Sim-to-Real Transfer of Navigation Policies
How Transferable Are Features in Convolutional Neural Network Acoustic Models across Languages
Representation Mixing for TTS Synthesis
The Pytorch-kaldi Speech Recognition Toolkit
Reproducibility in Machine Learning
AI for Social Good
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length
Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks
A Highly Adaptive Acoustic Model for Accurate Multi-dialect Speech Recognition
2019-04
Compositional generalization in a deep seq2seq model by separating syntax and semantics.
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)]Reinforced Imitation in Heterogeneous Action Space.
Learning Problem-Agnostic Speech Representations from Multiple Self-Supervised Tasks.
2019-03
InfoMask: Masked Variational Latent Representation to Localize Chest Disease
Towards Standardization of Data Licenses: The Montreal Data License
Online continual learning with no task boundaries.
Gated Orthogonal Recurrent Units: On Learning to Forget
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future.
2019-02
Hyperbolic Discounting and Learning over Multiple Horizons
2019-01
InfoBot: Transfer and Exploration via the Information Bottleneck
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies
Maximum Entropy Generators for Energy-Based Models.
Equivalence of Equilibrium Propagation and Recurrent Backpropagation.
Neural Computation
(2019-01-18)
direct.mit.eduPDF[Also on 2018 Conference on Cognitive Computational Neuroscience (2018-01-01)]The Benefits of Over-parameterization at Initialization in Deep ReLU Networks
InfoBot: Structured Exploration in ReinforcementLearning Using Information Bottleneck
On Adversarial Mixup Resynthesis
InfoBot: Transfer and Exploration via the Information Bottleneck
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Adversarial domain adaptation for stable brain-machine interfaces
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Gradient based sample selection for online continual learning
Wasserstein Dependency Measure for Representation Learning
2018-12
Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks.
Speech and Speaker Recognition from Raw Waveform with SincNet
The effects of negative adaptation in Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
MetaGAN: an adversarial approach to few-shot learning
Dendritic cortical microcircuits approximate the backpropagation algorithm
Deep convolutional networks for quality assessment of protein folds.
2018-11
Keep Drawing It: Iterative language-based image generation and editing
Interpretable Convolutional Filters with SincNet
2018-10
BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop.
Deep Learning. Das umfassende Handbuch
2018-09
EnGAN: Latent Space MCMC and Maximum Entropy Generators for Energy-based Models
Learning powerful policies and better dynamics models by encouraging consistency
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
h-detach: Modifying the LSTM Gradient Towards Better Optimization
ICLR 2018
(2018-09-27)
ui.adsabs.harvard.eduPDF[LATEST on arXiv preprint arXiv:1810.03023 (2018-10-06)]Manifold Mixup: Learning Better Representations by Interpolating Hidden States
Quaternion Recurrent Neural Networks
Probabilistic Planning with Sequential Monte Carlo methods
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
How can deep learning advance computational modeling of sensory information processing
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
On the Learning Dynamics of Deep Neural Networks.
Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding
2018-08
Learning deep representations by mutual information estimation and maximization
Generalization of Equilibrium Propagation to Vector Field Dynamics.
2018-07
Predicting Solution Summaries to Integer Linear Programs under Imperfect Information with Machine Learning.
Speaker Recognition from Raw Waveform with SincNet
DNN's Sharpest Directions Along the SGD Trajectory.
Feature-wise transformations
MaD TwinNet: Masker-Denoiser Architecture with Twin Networks for Monaural Sound Source Separation
Focused Hierarchical RNNs for Conditional Sequence Processing
Mutual Information Neural Estimation.
Neural models for key phrase detection and question generation
2018-06
On the Spectral Bias of Deep Neural Networks
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)]Modularity Matters: Learning Invariant Relational Reasoning Tasks
Towards Gene Expression Convolutions using Gene Interaction Graphs
Manifold Mixup: Better Representations by Interpolating Hidden States.
Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer.
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
Mine: mutual information neural estimation
Learning to rank for censored survival data.
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
(2018-06-01)
www.aclweb.org[Also on arXiv preprint arXiv:1804.09259 (2018-04-24)]On the Iterative Refinement of Densely Connected Representation Levels for Semantic Segmentation
2018-05
Image-to-image translation for cross-domain disentanglement
Generalization 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)]Towards End-to-end Spoken Language Understanding
Monaural Singing Voice Separation with Skip-Filtering Connections and Recurrent Inference of Time-Frequency Mask
Iteratively unveiling new regions of interest in Deep Learning models
Convolutional neural networks for mesh-based parcellation of the cerebral cortex
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)]Drawing and Recognizing Chinese Characters with Recurrent Neural Network
2018-03
Learning Anonymized Representations with Adversarial Neural Networks
Light Gated Recurrent Units for Speech Recognition
2018-02
Disentangling the independently controllable factors of variation by interacting with the world
A Walk with SGD.
Generalization in Machine Learning via Analytical Learning Theory
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 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
Graph Attention Networks
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 Normalized Inputs for Iterative Estimation in Medical Image Segmentation
2018-01
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.
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
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding
Introduction to NIPS 2017 Competition Track
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
