Publications

Michael Ahn*, Anthony Brohan*, Noah Brown*, Yevgen Chebotar*, Omar Cortes*, Byron David*, Chelsea Finn*, Keerthana Gopalakrishnan*, Karol Hausman*, Alex Herzog*, Daniel Ho*, Jasmine Hsu*, Julian Ibarz*, Brian Ichter*, Alex Irpan*, Eric Jang*, Rosario Jauregui Ruano*, Kyle Jeffrey*, Sally Jesmonth*, Nikhil 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* (2022). Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. SayCan.

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Yuqing Du, Daniel Ho, Alexander A. Alemi, Eric Jang, Mohi Khansari (2022). Bayesian Imitation Learning for End-to-End Mobile Manipulation. VIB.

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

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Yifeng Jiang, Tingnan Zhang, Daniel Ho, Yunfei Bai, C. Karen Liu, Sergey Levine, Jie Tan (2021). SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning. SimGAN.

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Zhuo Xu, Wenhao Yu, Alexander Herzog, Wenlong Lu, Chuyuan Fu, Masayoshi Tomizuka, Yunfei Bai, C. Karen Liu, Daniel Ho (2020). COCOI: Contact-aware Online Context Inference for Generalizable Non-planar Pushing. COCOI.

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Daniel Ho, Kanishka Rao, Zhuo Xu, Eric Jang, Mohi Khansari, Yunfei Bai (2020). RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer. RetinaGAN.

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Daniel Ho, Eric Liang, Ion Stoica, Pieter Abbeel, Xi Chen (2019). Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. Population Based Augmentation.

PDF Code Slides Towards Data Science BAIR Blog

T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen (2017). Improvements to context based self-supervised learning. Improvements to context based self-supervised learning.

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