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2021-05
Iterated learning for emergent systematicity in VQA
Learning Task Decomposition with Order-Memory Policy Network
Data-Efficient Reinforcement Learning with Self-Predictive Representations
Neural Approximate Sufficient Statistics for Implicit Models
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Systematic generalisation with group invariant predictions
2021-03
Learning Task Decomposition with Ordered Memory Policy Network.
2021-01
Emergent Communication under Competition
2020-12
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
2020-11
Gradient Starvation: A Learning Proclivity in Neural Networks
Unsupervised Learning of Dense Visual Representations.
Recursive Top-Down Production for Sentence Generation with Latent Trees
Supervised Seeded Iterated Learning for Interactive Language Learning
2020-10
Generative adversarial networks
NU-GAN: High resolution neural upsampling with GAN
Explicitly Modeling Syntax in Language Model improves Generalization
Neural Approximate Sufficient Statistics for Implicit Models.
Recursive Top-Down Production for Sentence Generation with Latent Trees.
Supervised Seeded Iterated Learning for Interactive Language Learning.
2020-09
Integrating Categorical Semantics into Unsupervised Domain Translation
SSW-GAN: Scalable Stage-wise Training of Video GANs
2020-07
Data-Efficient Reinforcement Learning with Momentum Predictive Representations
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
2020-03
Countering Language Drift with Seeded Iterated Learning.
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
Out-of-Distribution Generalization via Risk Extrapolation (REx)
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.
Detecting semantic anomalies
2020-01
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation.
Unsupervised Learning of Dense Visual Representations
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)]Ordered Memory
No-Press Diplomacy: Modeling Multi-Agent Gameplay
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
2019-11
Selective Brain Damage: Measuring the Disparate Impact of Model Pruning
What Do Compressed Deep Neural Networks Forget
Deep Generative Modeling of LiDAR Data
2019-10
Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery.
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
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.
Hierarchical Importance Weighted Autoencoders
On the Spectral Bias of Neural Networks
2019-05
Representation Mixing for TTS Synthesis
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
2019-01
Maximum Entropy Generators for Energy-Based Models.
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)]2018-12
Improving Explorability in Variational Inference with Annealed Variational Objectives
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
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
2018-08
Approximate Exploration through State Abstraction.
2018-07
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
Neural Autoregressive Flows
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Mutual Information Neural Estimator
Feature-wise transformations
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.
2018-04
Neural Autoregressive Flows
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
MINE: Mutual Information Neural Estimation
Learning Generative Models with Locally Disentangled Latent Factors
Inferring Identity Factors for Grouped Examples
FiLM: Visual Reasoning with a General Conditioning Layer
2018-01
HoME: a Household Multimodal Environment.
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