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2021-12
Gradient Starvation: A Learning Proclivity in Neural Networks
Pretraining Representations for Data-Efficient Reinforcement Learning
2021-11
Multi-label Iterated Learning for Image Classification with Label Ambiguity
2021-10
Chunked Autoregressive GAN for Conditional Waveform Synthesis
Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond.
2021-09
Overcoming Label Ambiguity with Multi-label Iterated Learning
2021-08
Deep Reinforcement Learning at the Edge of the Statistical Precipice
2021-07
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Continuous Coordination As a Realistic Scenario for Lifelong Learning
2021-06
Haptics-based Curiosity for Sparse-reward Tasks
A Variational Perspective on Diffusion-Based Generative Models and Score Matching
Hierarchical Video Generation for Complex Data.
2021-05
Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle.
Understanding by Understanding Not: Modeling Negation in Language Models.
SSW-GAN: Scalable Stage-wise Training of Video GANs
StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Iterated learning for emergent systematicity in VQA
Learning Task Decomposition with Order-Memory Policy Network
Systematic generalisation with group invariant predictions
Integrating Categorical Semantics into Unsupervised Domain Translation
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Neural Approximate Sufficient Statistics for Implicit Models
Data-Efficient Reinforcement Learning with Self-Predictive Representations
ICLR 2021
(2021-05-03)
papyrus.bib.umontreal.caPDF[Also on arXiv preprint arXiv:2007.05929 (2020-07-12)]2021-04
Touch-based Curiosity for Sparse-Reward Tasks.
2021-03
Learning Task Decomposition with Ordered Memory Policy Network.
Pretraining Reward-Free Representations for Data-Efficient Reinforcement Learning
2021-01
Generative Compositional Augmentations for Scene Graph Prediction
Emergent Communication under Competition.
Autonomous Agents and Multi-Agent Systems
(2021-01-01)
dl.acm.org[LATEST on arXiv preprint arXiv:2101.10276 (2021-01-25)]2020-11
Bijective-Contrastive Estimation
Gradient Starvation: A Learning Proclivity in Neural Networks
Recursive Top-Down Production for Sentence Generation with Latent Trees
Supervised Seeded Iterated Learning for Interactive Language Learning
Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images Using a View-Based Representation
International Journal of Computer Vision
(2020-11-01)
link.springer.com[Also on arXiv: Computer Vision and Pattern Recognition (2020-03-23)]2020-10
Generative adversarial networks
NU-GAN: High resolution neural upsampling with GAN.
Explicitly Modeling Syntax in Language Model improves Generalization.
Recursive Top-Down Production for Sentence Generation with Latent Trees.
Integrating Categorical Semantics into Unsupervised Domain Translation
2020-07
Data-Efficient Reinforcement Learning with Momentum Predictive Representations. (arXiv:2007.05929v2 [cs.LG] UPDATED)
arXiv Computer Science
(2020-07-24)
Data-Efficient Reinforcement Learning with Momentum Predictive Representations
Countering Language Drift with Seeded Iterated Learning
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
Generative Graph Perturbations for Scene Graph Prediction.
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
2020-05
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation
2020-04
On Bonus Based Exploration Methods In The Arcade Learning Environment
Detecting Semantic Anomalies
2020-03
Countering Language Drift with Seeded Iterated Learning
2020-02
Solving ODE with Universal Flows: Approximation Theory for Flow-Based Models
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models.
2020-01
Unsupervised Learning of Dense Visual Representations
What Do Compressed Deep Neural Networks Forget
2019-12
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)]2019-11
Selective Brain Damage: Measuring the Disparate Impact of Model Pruning
Ordered Memory
Deep Generative Modeling of LiDAR Data
2019-10
Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery.
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering
Improved Conditional VRNNs for Video Prediction
Batch Weight for Domain Adaptation With Mass Shift
2019-09
Selfish Emergent Communication
{COMPANYNAME}11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
No Press Diplomacy: Modeling Multi-Agent Gameplay
No-Press Diplomacy: Modeling Multi-Agent Gameplay
2019-08
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment
2019-06
Adversarial Computation of Optimal Transport Maps
Investigating Biases in Textual Entailment Datasets.
Note on the bias and variance of variational inference.
2019-05
On the Spectral Bias of Neural Networks
Hierarchical Importance Weighted Autoencoders
ICML 2019
(2019-05-13)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:1905.04866 (2019-05-13)]Representation Mixing for TTS Synthesis
Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Reproducibility in Machine Learning
2019-03
Counterpoint by Convolution
2019-01
Maximum Entropy Generators for Energy-Based Models.
Probability Distillation: A Caveat and Alternatives.
Stochastic Neural Network with Kronecker Flow.
AISTATS 2019
(2019-01-01)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:1906.04282 (2019-06-10)]2018-12
Towards Text Generation with Adversarially Learned Neural Outlines
2018-11
Planning in Dynamic Environments with Conditional Autoregressive Models.
Harmonic Recomposition using Conditional Autoregressive Modeling.
Blindfold Baselines for Embodied QA.
2018-10
Sim-to-Real Transfer with Neural-Augmented Robot Simulation
Deep Learning. Das umfassende Handbuch
2018-09
EnGAN: Latent Space MCMC and Maximum Entropy Generators for Energy-based Models
On Difficulties of Probability Distillation
W2GAN: RECOVERING AN OPTIMAL TRANSPORT MAP WITH A GAN
Pix2Scene: Learning Implicit 3D Representations from Images
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
ICLR 2018
(2018-09-27)
ui.adsabs.harvard.eduPDF[LATEST on arXiv preprint arXiv:1810.09536 (2018-10-22)]Systematic Generalization: What Is Required and Can It Be Learned?
Unsupervised one-to-many image translation
Convergence Properties of Deep Neural Networks on Separable Data
Manifold Mixup: Learning Better Representations by Interpolating Hidden States
On the Learning Dynamics of Deep Neural Networks.
Visual Reasoning with Multi-hop Feature Modulation
Improving Explorability in Variational Inference with Annealed Variational Objectives
2018-08
Approximate Exploration through State Abstraction.
2018-07
Feature-wise transformations
Neural Autoregressive Flows
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Mutual Information Neural Estimation.
2018-06
On the Spectral Bias of Deep Neural Networks
Learning Distributed Representations from Reviews for Collaborative Filtering
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
2018-03
Generating Contradictory, Neutral, and Entailing Sentences
2018-02
Hierarchical Adversarially Learned Inference
Bayesian Hypernetworks
Neural Language Modeling by Jointly Learning Syntax and Lexicon
Learning Generative Models with Locally Disentangled Latent Factors
Inferring Identity Factors for Grouped Examples
FiLM: Visual Reasoning with a General Conditioning Layer.
2018-01
MINE: Mutual Information Neural Estimation.
HoME: a Household Multimodal Environment.
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