Depth Sweep Regression Forests for Estimating 3D Human Pose from Images. - Ilya Kostrikov; Jürgen Gall (BMVC, 2014)

Probabilistic Labeling Cost for High-Accuracy Multi-view Reconstruction. - Ilya Kostrikov; Esther Horbert; Bastian Leibe (CVPR, 2014)

An Efficient Convolutional Network for Human Pose Estimation. - Umer Rafi; Bastian Leibe; Juergen Gall; Ilya Kostrikov (BMVC, 2016)

PlaNet - Photo Geolocation with Convolutional Neural Networks. - Tobias Weyand; Ilya Kostrikov; James Philbin (ECCV (8), 2016)

Surface Networks. - Ilya Kostrikov; Joan Bruna; Daniele Panozzo; Denis Zorin (CoRR, 2017)

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. - Sainbayar Sukhbaatar; Ilya Kostrikov; Arthur Szlam; Rob Fergus (CoRR, 2017)

Surface Networks. - Ilya Kostrikov; Zhongshi Jiang; Daniele Panozzo; Denis Zorin; Joan Bruna (CVPR, 2018)

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. - Sainbayar Sukhbaatar; Zeming Lin; Ilya Kostrikov; Gabriel Synnaeve; Arthur Szlam; Rob Fergus (ICLR (Poster), 2018)

Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning. - Ilya Kostrikov; Kumar Krishna Agrawal; Sergey Levine; Jonathan Tompson (CoRR, 2018)

Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning. - Ilya Kostrikov; Kumar Krishna Agrawal; Debidatta Dwibedi; Sergey Levine; Jonathan Tompson (ICLR (Poster), 2019)

AlgaeDICE: Policy Gradient from Arbitrary Experience. - Ofir Nachum; Bo Dai 001; Ilya Kostrikov; Yinlam Chow; Lihong Li 001; Dale Schuurmans (CoRR, 2019)

Imitation Learning via Off-Policy Distribution Matching. - Ilya Kostrikov; Ofir Nachum; Jonathan Tompson (ICLR, 2020)

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

Statistical Bootstrapping for Uncertainty Estimation in Off-Policy Evaluation. - Ilya Kostrikov; Ofir Nachum (CoRR, 2020)

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)

Offline Reinforcement Learning with Fisher Divergence Critic Regularization. - Ilya Kostrikov; Rob Fergus; Jonathan Tompson; Ofir Nachum (ICML, 2021)

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

Improving Sample Efficiency of Imitation and Reinforcement Learning. - Ilya Kostrikov (2021)

Offline Reinforcement Learning for Visual Navigation. - Dhruv Shah; Arjun Bhorkar; Hrishit Leen; Ilya Kostrikov; Nicholas Rhinehart; Sergey Levine (CoRL, 2022)

RvS: What is Essential for Offline RL via Supervised Learning? - Scott Emmons; Benjamin Eysenbach; Ilya Kostrikov; Sergey Levine (ICLR, 2022)

Offline Reinforcement Learning with Implicit Q-Learning. - Ilya Kostrikov; Ashvin Nair; Sergey Levine (ICLR, 2022)

In Defense of the Unitary Scalarization for Deep Multi-Task Learning. - Vitaly Kurin; Alessandro De Palma; Ilya Kostrikov; Shimon Whiteson; Pawan Kumar Mudigonda (NeurIPS, 2022)

Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions. - Bogdan Mazoure; Ilya Kostrikov; Ofir Nachum; Jonathan Tompson (NeurIPS, 2022)

In Defense of the Unitary Scalarization for Deep Multi-Task Learning. - Vitaly Kurin; Alessandro De Palma; Ilya Kostrikov; Shimon Whiteson; M. Pawan Kumar (CoRR, 2022)

A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning. - Laura M. Smith; Ilya Kostrikov; Sergey Levine (CoRR, 2022)

FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing. - Kyle Stachowicz; Dhruv Shah; Arjun Bhorkar; Ilya Kostrikov; Sergey Levine (CoRL, 2023)

Efficient Deep Reinforcement Learning Requires Regulating Overfitting. - Qiyang Li; Aviral Kumar; Ilya Kostrikov; Sergey Levine (ICLR, 2023)

Offline RL for Natural Language Generation with Implicit Language Q Learning. - Charlie Snell; Ilya Kostrikov; Yi Su; Sherry Yang 001; Sergey Levine (ICLR, 2023)

Efficient Online Reinforcement Learning with Offline Data. - Philip J. Ball; Laura M. Smith; Ilya Kostrikov; Sergey Levine (ICML, 2023)

Demonstrating A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning. - Ilya Kostrikov; Laura M. Smith; Sergey Levine (Robotics: Science and Systems, 2023)

IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies. - Philippe Hansen-Estruch; Ilya Kostrikov; Michael Janner; Jakub Grudzien Kuba; Sergey Levine (CoRR, 2023)

Training Diffusion Models with Reinforcement Learning. - Kevin Black; Michael Janner; Yilun Du; Ilya Kostrikov; Sergey Levine (ICLR, 2024)

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. - Rafael Rafailov; Kyle Beltran Hatch; Anikait Singh; Aviral Kumar; Laura M. Smith; Ilya Kostrikov; Philippe Hansen-Estruch; Victor Kolev; Philip J. Ball; Jiajun Wu 001; Sergey Levine; Chelsea Finn (RLJ, 2024)