Denis Yarats

I am a PhD student at New York University advised by Rob Fergus and Lerrel Pinto and at Facebook AI Research advised by Alessandro Lazaric.
I am also a visiting PhD student at UC Berkeley RLL with Pieter Abbeel.
I am interested in representation learning in image-based RL to enable better sample efficiency and generalization.
[Google Scholar] [GitHub] [CV] [denisyarats at cs dot nyu dot edu]

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Publications

Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning.
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto.
ArXiv 2021.
[PDF] [arXiv] [Code]

Reinforcement Learning with Prototypical Representations.
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto.
ICML 2021. SSL-RL Workshop at ICLR 2021 (Spotlight).
[PDF] [arXiv] [Code]

Learning Navigation Skills for Legged Robots with Learned Robot Embeddings.
Joanne Truong, Denis Yarats, Tianyu Li, Franziska Meier, Sonia Chernova, Dhruv Batra, Akshara Rai.
Submitted to ICRA 2021.
[PDF] [arXiv]

On the Model-Based Stochastic Value Gradient for Continuous Reinforcement Learning.
Brandon Amos, Sam Stanton, Denis Yarats, Andrew Wilson.
L4DC 2021 (Oral).
[PDF] [arXiv] [Website]

Automatic Data Augmentation for Generalization in Deep Reinforcement Learning.
Roberta Raileanu, Max Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus.
BIG Workshop at ICML 2020 (Oral).
[PDF] [arXiv] [Code] [Website]

Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels.
Denis Yarats*, Ilya Kostrikov*, Rob Fergus.
ICLR 2021 (Spotlight).
[PDF] [arXiv] [Code] [Website]

On the adequacy of untuned warmup for adaptive optimization.
Jerry Ma, Denis Yarats.
AAAI 2021.
[PDF] [arXiv]

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images.
Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus.
AAAI 2021.
[PDF] [arXiv] [Code] [Website]

The Differentiable Cross-Entropy Method.
Brandon Amos, Denis Yarats.
ICML 2020.
[PDF] [arXiv] [Website]

Generalized Inner Loop Meta-Learning.
Edward Grefenstette, Brandon Amos, Denis Yarats, Phu Mon Htut, Artem Molchanov
Franziska Meier, Douwe Kiela, Kyunghyun Cho, Soumith Chintala.
ArXiv 2019.
[PDF] [arXiv] [Code] [Website]

Hierarchical Decision Making by Generating and Following Natural Language Instructions.
Hengyuan Hu*, Denis Yarats*, Qucheng Gong, Yuandong Tian, Mike Lewis.
NeurIPS 2019.
[PDF] [arXiv] [Code] [Website] [Blog]

Quasi-hyperbolic momentum and Adam for deep learning.
Jerry Ma, Denis Yarats.
ICLR 2019.
[PDF] [arXiv] [Code] [Website]

Hierarchical Text Generation and Planning for Strategic Dialogue.
Denis Yarats, Mike Lewis.
ICML 2018.
[PDF] [arXiv] [Code]

Deal or No Deal? End-to-End Learning for Negotiation Dialogues.
Mike Lewis, Denis Yarats, Yann Dauphin, Devi Parikh, Dhruv Batra.
EMNLP 2017.
[PDF] [arXiv] [Code]

Convolutional Sequence to Sequence Learning.
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann Dauphin.
ICML 2017.
[PDF] [arXiv] [Code]

Code

PyTorch implementation of Soft Actor-Critic.
Denis Yarats, Ilya Kostrikov.
[Code]

OpenAI Gym wrapper for the DeepMind Control Suite.
Denis Yarats.
[Code]