End-to-End Learning of Semantic Grasping. - Eric Jang; Sudheendra Vijayanarasimhan; Peter Pastor; Julian Ibarz; Sergey Levine (CoRL, 2017)

Categorical Reparameterization with Gumbel-Softmax. - Eric Jang; Shixiang Gu; Ben Poole (ICLR (Poster), 2017)

Sim2Real View Invariant Visual Servoing by Recurrent Control. - Fereshteh Sadeghi; Alexander Toshev; Eric Jang; Sergey Levine (CoRR, 2017)

Grasp2Vec: Learning Object Representations from Self-Supervised Grasping. - Eric Jang; Coline Devin; Vincent Vanhoucke; Sergey Levine (CoRL, 2018)

Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. - Dmitry Kalashnikov; Alex Irpan; Peter Pastor; Julian Ibarz; Alexander Herzog; Eric Jang; Deirdre Quillen; Ethan Holly; Mrinal Kalakrishnan; Vincent Vanhoucke; Sergey Levine (CoRL, 2018)

Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control. - Fereshteh Sadeghi; Alexander Toshev; Eric Jang; Sergey Levine (CVPR, 2018)

Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. - Deirdre Quillen; Eric Jang; Ofir Nachum; Chelsea Finn; Julian Ibarz; Sergey Levine (ICRA, 2018)

Time-Contrastive Networks: Self-Supervised Learning from Video. - Pierre Sermanet; Corey Lynch; Yevgen Chebotar; Jasmine Hsu; Eric Jang; Stefan Schaal; Sergey Levine (ICRA, 2018)

QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. - Dmitry Kalashnikov; Alex Irpan; Peter Pastor; Julian Ibarz; Alexander Herzog; Eric Jang; Deirdre Quillen; Ethan Holly; Mrinal Kalakrishnan; Vincent Vanhoucke; Sergey Levine (CoRR, 2018)

Generative Ensembles for Robust Anomaly Detection. - Hyunsun Choi; Eric Jang (CoRR, 2018)

Watch, Try, Learn: Meta-Learning from Demonstrations and Reward. - Allan Zhou; Eric Jang; Daniel Kappler; Alexander Herzog; Mohi Khansari; Paul Wohlhart; Yunfei Bai; Mrinal Kalakrishnan; Sergey Levine; Chelsea Finn (CoRR, 2019)

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. - Ted Xiao; Eric Jang; Dmitry Kalashnikov; Sergey Levine; Julian Ibarz; Karol Hausman; Alexander Herzog (ICLR, 2020)

Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards. - Allan Zhou; Eric Jang; Daniel Kappler; Alexander Herzog; Mohi Khansari; Paul Wohlhart; Yunfei Bai; Mrinal Kalakrishnan; Sergey Levine; Chelsea Finn (ICLR, 2020)

Scalable Multi-Task Imitation Learning with Autonomous Improvement. - Avi Singh; Eric Jang; Alexander Irpan; Daniel Kappler; Murtaza Dalal; Sergey Levine; Mohi Khansari; Chelsea Finn (ICRA, 2020)

Meta-Learning Requires Meta-Augmentation. - Janarthanan Rajendran; Alexander Irpan; Eric Jang (NeurIPS, 2020)

BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning. - Eric Jang; Alex Irpan; Mohi Khansari; Daniel Kappler; Frederik Ebert; Corey Lynch; Sergey Levine; Chelsea Finn (CoRL, 2021)

AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale. - Yao Lu 006; Karol Hausman; Yevgen Chebotar; Mengyuan Yan; Eric Jang; Alexander Herzog; Ted Xiao; Alex Irpan; Mohi Khansari; Dmitry Kalashnikov; Sergey Levine (CoRL, 2021)

RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer. - Daniel Ho; Kanishka Rao; Zhuo Xu; Eric Jang; Mohi Khansari; Yunfei Bai (ICRA, 2021)

AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale. - Yao Lu 006; Karol Hausman; Yevgen Chebotar; Mengyuan Yan; Eric Jang; Alexander Herzog; Ted Xiao; Alex Irpan; Mohi Khansari; Dmitry Kalashnikov; Sergey Levine (CoRR, 2021)

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. - Brian Ichter; Anthony Brohan; Yevgen Chebotar; Chelsea Finn; Karol Hausman; Alexander Herzog; Daniel Ho; Julian Ibarz; Alex Irpan; Eric Jang; Ryan Julian; Dmitry Kalashnikov; et al. (CoRL, 2022)

Bayesian Imitation Learning for End-to-End Mobile Manipulation. - Yuqing Du; Daniel Ho; Alex Alemi; Eric Jang; Mohi Khansari (ICML, 2022)

Multi-Game Decision Transformers. - Kuang-Huei Lee; Ofir Nachum; Mengjiao Yang 001; Lisa Lee; Daniel Freeman; Sergio Guadarrama; Ian Fischer; Winnie Xu; Eric Jang; Henryk Michalewski; Igor Mordatch (NeurIPS, 2022)

Practical Imitation Learning in the Real World via Task Consistency Loss. - Mohi Khansari; Daniel Ho; Yuqing Du; Armando Fuentes; Matthew Bennice; Nicolas Sievers; Sean Kirmani; Yunfei Bai; Eric Jang (CoRR, 2022)

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. - Michael Ahn; Anthony Brohan; Noah Brown; Yevgen Chebotar; Omar Cortes; Byron David; Chelsea Finn; Keerthana Gopalakrishnan; Karol Hausman; Alexander Herzog; Daniel Ho; Jasmine Hsu; et al. (CoRR, 2022)

Practical Visual Deep Imitation Learning via Task-Level Domain Consistency. - Mohi Khansari; Daniel Ho; Yuqing Du; Armando Fuentes; Matthew Bennice; Nicolas Sievers; Sean Kirmani; Yunfei Bai; Eric Jang (ICRA, 2023)