Denis Yarats


I am a PhD student at New York University and FAIR working with Rob Fergus.
My research interests broadly include Reinforcement Learning, Optimal Control, and Robotics.
[Google Scholar] [GitHub] [CV] [denisyarats at cs dot nyu dot edu]

Publications

On the adequacy of untuned warmup for adaptive optimization.
Jerry Ma, Denis Yarats.
Submitted to AISTATS 2020.
[PDF] [arXiv]

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images.
Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus.
Submitted to ICLR 2020.
[PDF] [arXiv] [Code] [Website]

The Differentiable Cross-Entropy Method.
Brandon Amos, Denis Yarats.
Submitted to ICLR 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.
Submitted to ICLR 2020.
[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]