Eric Jang

According to our database, Eric Jang authored at least 25 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

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

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

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, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan

CoRR, 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

Multi-Game Decision Transformers.

Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, Igor Mordatch

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bayesian Imitation Learning for End-to-End Mobile Manipulation.

Yuqing Du, Daniel Ho, Alex Alemi, Eric Jang, Mohi Khansari

Proceedings of the International Conference on Machine Learning, 2022

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, Sergey Levine, Yao Lu, Carolina Parada, Kanishka Rao, Pierre Sermanet, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Mengyuan Yan, Noah Brown, Michael Ahn, Omar Cortes, Nicolas Sievers, Clayton Tan, Sichun Xu, Diego Reyes, Jarek Rettinghouse, Jornell Quiambao, Peter Pastor, Linda Luu, Kuang-Huei Lee, Yuheng Kuang, Sally Jesmonth, Nikhil J. Joshi, Kyle Jeffrey, Rosario Jauregui Ruano, Jasmine Hsu, Keerthana Gopalakrishnan, Byron David, Andy Zeng, Chuyuan Kelly Fu

Proceedings of the Conference on Robot Learning, 2022

2021

AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale.

Yao Lu, Karol Hausman, Yevgen Chebotar, Mengyuan Yan, Eric Jang, Alexander Herzog, Ted Xiao, Alex Irpan, Mohi Khansari, Dmitry Kalashnikov, Sergey Levine

CoRR, 2021

RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer.

Daniel Ho, Kanishka Rao, Zhuo Xu, Eric Jang, Mohi Khansari, Yunfei Bai

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale.

Yao Lu, Karol Hausman, Yevgen Chebotar, Mengyuan Yan, Eric Jang, Alexander Herzog, Ted Xiao, Alex Irpan, Mohi Khansari, Dmitry Kalashnikov, Sergey Levine

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

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

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Meta-Learning Requires Meta-Augmentation.

Janarthanan Rajendran, Alexander Irpan, Eric Jang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 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

Proceedings of the 8th International Conference on Learning Representations, 2020

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control.

Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

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

2018

Generative Ensembles for Robust Anomaly Detection.

Hyunsun Choi, Eric Jang

CoRR, 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

Time-Contrastive Networks: Self-Supervised Learning from Video.

Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 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

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control.

Fereshteh Sadeghi, Alexander Toshev, Eric Jang, Sergey Levine

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Grasp2Vec: Learning Object Representations from Self-Supervised Grasping.

Eric Jang, Coline Devin, Vincent Vanhoucke, Sergey Levine

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Sim2Real View Invariant Visual Servoing by Recurrent Control.

Fereshteh Sadeghi, Alexander Toshev, Eric Jang, Sergey Levine

CoRR, 2017

Categorical Reparameterization with Gumbel-Softmax.

Eric Jang, Shixiang Gu, Ben Poole

Proceedings of the 5th International Conference on Learning Representations, 2017

End-to-End Learning of Semantic Grasping.

Eric Jang, Sudheendra Vijayanarasimhan, Peter Pastor, Julian Ibarz, Sergey Levine

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017