Deal or No Deal? End-to-End Learning of Negotiation Dialogues. - Mike Lewis; Denis Yarats; Yann N. Dauphin; Devi Parikh; Dhruv Batra (EMNLP, 2017)

Convolutional Sequence to Sequence Learning. - Jonas Gehring; Michael Auli; David Grangier; Denis Yarats; Yann N. Dauphin (ICML, 2017)

Hierarchical Text Generation and Planning for Strategic Dialogue. - Denis Yarats; Mike Lewis (ICML, 2018)

Quasi-hyperbolic momentum and Adam for deep learning. - Jerry Ma; Denis Yarats (ICLR (Poster), 2019)

Hierarchical Decision Making by Generating and Following Natural Language Instructions. - Hengyuan Hu; Denis Yarats; Qucheng Gong; Yuandong Tian; Mike Lewis (NeurIPS, 2019)

Generalized Inner Loop Meta-Learning. - Edward Grefenstette; Brandon Amos; Denis Yarats; Phu Mon Htut; Artem Molchanov; Franziska Meier; Douwe Kiela; Kyunghyun Cho; Soumith Chintala (CoRR, 2019)

The Differentiable Cross-Entropy Method. - Brandon Amos; Denis Yarats (ICML, 2020)

Automatic Data Augmentation for Generalization in Deep Reinforcement Learning. - Roberta Raileanu; Maxwell Goldstein; Denis Yarats; Ilya Kostrikov; Rob Fergus (CoRR, 2020)

On the Adequacy of Untuned Warmup for Adaptive Optimization. - Jerry Ma; Denis Yarats (AAAI, 2021)

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. - Denis Yarats; Amy Zhang 001; Ilya Kostrikov; Brandon Amos; Joelle Pineau; Rob Fergus (AAAI, 2021)

Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. - Denis Yarats; Ilya Kostrikov; Rob Fergus (ICLR, 2021)

Reinforcement Learning with Prototypical Representations. - Denis Yarats; Rob Fergus; Alessandro Lazaric; Lerrel Pinto (ICML, 2021)

Learning Navigation Skills for Legged Robots with Learned Robot Embeddings. - Joanne Truong; Denis Yarats; Tianyu Li; Franziska Meier; Sonia Chernova; Dhruv Batra; Akshara Rai (IROS, 2021)

On the model-based stochastic value gradient for continuous reinforcement learning. - Brandon Amos; Samuel Stanton; Denis Yarats; Andrew Gordon Wilson (L4DC, 2021)

Real Robot Challenge: A Robotics Competition in the Cloud. - Stefan Bauer; Manuel Wüthrich; Felix Widmaier; Annika Buchholz; Sebastian Stark; Anirudh Goyal; Thomas Steinbrenner; Joel Akpo; Shruti Joshi; Vincent Berenz; Vaibhav Agrawal; Niklas Funk; et al. (NeurIPS (Competition and Demos), 2021)

URLB: Unsupervised Reinforcement Learning Benchmark. - Michael Laskin; Denis Yarats; Hao Liu 055; Kimin Lee; Albert Zhan; Kevin Lu; Catherine Cang; Lerrel Pinto; Pieter Abbeel (NeurIPS Datasets and Benchmarks, 2021)

Automatic Data Augmentation for Generalization in Reinforcement Learning. - Roberta Raileanu; Maxwell Goldstein; Denis Yarats; Ilya Kostrikov; Rob Fergus (NeurIPS, 2021)

A Robot Cluster for Reproducible Research in Dexterous Manipulation. - Stefan Bauer; Felix Widmaier; Manuel Wüthrich; Niklas Funk; Julen Urain De Jesus; Jan Peters 001; Joe Watson; Claire Chen; Krishnan Srinivasan; Junwu Zhang; Jeffrey Zhang 005; Matthew R. Walter; et al. (CoRR, 2021)

Watch and Match: Supercharging Imitation with Regularized Optimal Transport. - Siddhant Haldar; Vaibhav Mathur; Denis Yarats; Lerrel Pinto (CoRL, 2022)

Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. - Denis Yarats; Rob Fergus; Alessandro Lazaric; Lerrel Pinto (ICLR, 2022)

Unsupervised Reinforcement Learning with Contrastive Intrinsic Control. - Michael Laskin; Hao Liu 055; Xue Bin Peng; Denis Yarats; Aravind Rajeswaran; Pieter Abbeel (NeurIPS, 2022)

Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning. - Denis Yarats; David Brandfonbrener; Hao Liu 055; Michael Laskin; Pieter Abbeel; Alessandro Lazaric; Lerrel Pinto (CoRR, 2022)

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery. - Michael Laskin; Hao Liu 055; Xue Bin Peng; Denis Yarats; Aravind Rajeswaran; Pieter Abbeel (CoRR, 2022)