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2021-06
Multi-Resolution Continuous Normalizing Flows.
Beyond Target Networks: Improving Deep Q-learning with Functional Regularization.
DuoRAT: Towards Simpler Text-to-SQL Models
2021-05
Visual Question Answering From Another Perspective: CLEVR Mental Rotation Tests
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
Dependency Structure Discovery from Interventions
Mem2Mem: Learning to Summarize Long Texts with Memory Compression and Transfer
Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks
Predicting Infectiousness for Proactive Contact Tracing
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data
Reinforcement Learning with Random Delays
2021-03
Accounting for Variance in Machine Learning Benchmarks
Fourth Conference on Machine Learning and Systems ( MLsys 2021)
(2021-03-15)
proceedings.mlsys.orgPDF[Also on arXiv preprint arXiv:2103.03098 (2021-03-01)]2021-02
Autobots: Latent Variable Sequential Set Transformers
Latent Variable Nested Set Transformers & AutoBots.
2021-01
Structural Inductive Biases in Emergent Communication
Proceedings of the Annual Meeting of the Cognitive Science Society
(2021-01-01)
escholarship.org[Also on arXiv: Computation and Language (2020-02-04)]2020-11
Bijective-Contrastive Estimation
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
2020-10
COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing.
Predicting Infectiousness for Proactive Contact Tracing
Learning to Summarize Long Texts with Memory Compression and Transfer.
Reinforcement Learning with Random Delays
2020-09
Measuring Systematic Generalization in Neural Proof Generation with Transformers
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data
2020-08
Action-Based Representation Learning for Autonomous Driving
Leveraging cluster backbones for improving MAP inference in statistical relational models
2020-07
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
Robust motion in-betweening
ACM Transactions on Graphics
(2020-07-08)
dl.acm.org[LATEST on arXiv preprint arXiv:2102.04942 (2021-02-09)]Interactive Machine Comprehension with Information Seeking Agents.
Would you Rather? A New Benchmark for Learning Machine Alignment with Cultural Values and Social Preferences
2020-06
Medical Imaging with Deep Learning: MIDL 2020 - Short Paper Track.
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
CLAREL: Classification via Retrieval Loss for Zero-Shot Learning
2020-04
Reinforced active learning for image segmentation
ICLR 2020
(2020-04-30)
iclr.ccPDF[Also on arXiv: Computer Vision and Pattern Recognition (2020-02-16)]Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Role-Wise Data Augmentation for Knowledge Distillation.
Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning
2020-03
Towards Understanding Generalization in Gradient-Based Meta-Learning
2020-02
On the impressive performance of randomly weighted encoders in summarization tasks.
Curriculum in Gradient-Based Meta-Reinforcement Learning.
Exploring Structural Inductive Biases in Emergent Communication.
2019-12
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation
2019-11
Real-Time Reinforcement Learning
2019-10
Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments
Conference on Robot Learning
(2019-10-29)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1910.13249 (2019-10-29)]Neural Multisensory Scene Inference
2019-09
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
Learning Neural Causal Models from Unknown Interventions.
Learning Sparse Mixture of Experts for Visual Question Answering
Retrieving Signals with Deep Complex Extractors
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models.
2019-08
Interactive Language Learning by Question Answering
2019-07
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation.
On the impressive performance of randomly weighted encoders in summarization tasks
Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study
2019-06
Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments
2019-05
Fine-grained zero-shot recognition with metric rescaling.
Revision in Continuous Space: Fine-Grained Control of Text Style Transfer.
Structure Learning for Neural Module Networks.
EMNLP 2019
(2019-05-01)
ui.adsabs.harvard.eduPDF[LATEST on arXiv preprint arXiv:1905.11532 (2019-05-27)]2019-04
Active Domain Randomization
Conference on Robot Learning
(2019-04-09)
proceedings.mlr.pressPDF[Also on arXiv: Learning (2019-04-09)]2019-03
Dataflow-Based Joint Quantization for Deep Neural Networks
Towards Standardization of Data Licenses: The Montreal Data License
Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases
Adversarial Mixup Resynthesizers
2019-01
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
The Liver Tumor Segmentation Benchmark (LiTS)
Dataflow-based Joint Quantization of Weights and Activations for Deep Neural Networks
On Adversarial Mixup Resynthesis
2018-12
Deep Learning recognizes weather and climate patterns
Recurrent transition networks for character locomotion
Towards Text Generation with Adversarially Learned Neural Outlines
2018-11
A Survey of Mobile Computing for the Visually Impaired.
Towards Deep Conversational Recommendations
2018-10
Recurrent semi-supervised classification and constrained adversarial generation with motion capture data
2018-09
RNNs with Private and Shared Representations for Semi-Supervised Sequence Learning
Hiding Objects from Detectors: Exploring Transferrable Adversarial Patterns
Visualizing and Discovering Behavioural Weaknesses in Deep Reinforcement Learning
Visual Imitation Learning with Recurrent Siamese Networks.
Probabilistic Planning with Sequential Monte Carlo methods
Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding
2018-07
Focused Hierarchical RNNs for Conditional Sequence Processing
2018-06
Fashion-Gen: The Generative Fashion Dataset and Challenge
Improving Landmark Localization with Semi-Supervised Learning
2018-05
Convolutional networks for kidney segmentation in contrast-enhanced CT scans
Computer methods in biomechanics and biomedical engineering. Imaging & visualization
(2018-05-04)
doi.org2018-04
Liver lesion segmentation informed by joint liver segmentation
2018-03
Unsupervised Depth Estimation, 3D Face Rotation and Replacement
2018-02
Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks
Twin Networks: Matching the Future for Sequence Generation
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
Inferring Identity Factors for Grouped Examples
Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation
2018-01
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding
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