Tianhe Yu

74 papers A* 16A 1B 1Misc 8Journal 38Unranked 9
YearRankTypeTitle / Venue / Authors
2025 J jnl
Meta-World+: An Improved, Standardized, RL Benchmark.
CoRR
Reginald McLean, Evangelos Chatzaroulas, Luc McCutcheon, Frank Röder, Tianhe Yu, Zhanpeng He, K. R. Zentner, Ryan Julian, Jordan K. Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro
2025 A* conf
RRM: Robust Reward Model Training Mitigates Reward Hacking.
ICLR
Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasia Makarova, Jeremiah Zhe Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh
2024 A* conf
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.
ICRA
Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew E. Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey T. Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante-Gomez, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin
2024 J jnl
RRM: Robust Reward Model Training Mitigates Reward Hacking.
CoRR
Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasiia Makarova, Jeremiah Z. Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh
2024 Misc conf
RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches.
CoRL
Priya Sundaresan, Quan Vuong, Jiayuan Gu, Peng Xu, Ted Xiao, Sean Kirmani, Tianhe Yu, Michael Stark, Ajinkya Jain, Karol Hausman, Dorsa Sadigh, Jeannette Bohg, Stefan Schaal
2024 J jnl
RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches.
CoRR
Priya Sundaresan, Quan Vuong, Jiayuan Gu, Peng Xu, Ted Xiao, Sean Kirmani, Tianhe Yu, Michael Stark, Ajinkya Jain, Karol Hausman, Dorsa Sadigh, Jeannette Bohg, Stefan Schaal
2024 J jnl
ReARTSim: an ReRAM ARray Transient Simulator with GPU optimized runtime acceleration.
Neuromorph. Comput. Eng.
Yu Sui, Tianhe Yu, Shiming Song
2024 A* conf
Video Language Planning.
ICLR
Yilun Du, Sherry Yang, Pete Florence, Fei Xia, Ayzaan Wahid, Brian Ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Andy Zeng, Jonathan Tompson
2024 Misc conf
What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?
CoRL
Kaylee Burns, Zach Witzel, Jubayer Ibn Hamid, Tianhe Yu, Chelsea Finn, Karol Hausman
2023 — conf
Contrastive Example-Based Control.
L4DC
Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
2023 J jnl
Contrastive Example-Based Control.
CoRR
Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
2023 A* conf
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching.
AAAI
Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon
2023 J jnl
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching.
CoRR
Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon
2023 A* conf
PaLM-E: An Embodied Multimodal Language Model.
ICML
Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence
2023 J jnl
PaLM-E: An Embodied Multimodal Language Model.
CoRR
Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence
2023 Misc conf
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions.
CoRL
Yevgen Chebotar, Quan Vuong, Karol Hausman, Fei Xia, Yao Lu, Alex Irpan, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Anand Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine
2023 J jnl
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions.
CoRR
Yevgen Chebotar, Quan Vuong, Alex Irpan, Karol Hausman, Fei Xia, Yao Lu, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine
2023 — conf
RT-1: Robotics Transformer for Real-World Control at Scale.
Robotics: Science and Systems
Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag R. Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich
2023 Misc conf
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.
CoRL
Brianna Zitkovich, Tianhe Yu, Sichun Xu, Peng Xu, Ted Xiao, Fei Xia, Jialin Wu, Paul Wohlhart, Stefan Welker, Ayzaan Wahid, Quan Vuong, Vincent Vanhoucke, Huong T. Tran, Radu Soricut, Anikait Singh, Jaspiar Singh, Pierre Sermanet, Pannag R. Sanketi, Grecia Salazar, Michael S. Ryoo, Krista Reymann, Kanishka Rao, Karl Pertsch, Igor Mordatch, Henryk Michalewski, Yao Lu, Sergey Levine, Lisa Lee, Tsang-Wei Edward Lee, Isabel Leal, Yuheng Kuang, Dmitry Kalashnikov, Ryan Julian, Nikhil J. Joshi, Alex Irpan, Brian Ichter, Jasmine Hsu, Alexander Herzog, Karol Hausman, Keerthana Gopalakrishnan, Chuyuan Fu, Pete Florence, Chelsea Finn, Kumar Avinava Dubey, Danny Driess, Tianli Ding, Krzysztof Marcin Choromanski, Xi Chen, Yevgen Chebotar, Justice Carbajal, Noah Brown, Anthony Brohan, Montserrat Gonzalez Arenas, Kehang Han
2023 J jnl
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.
CoRR
Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, Pete Florence, Chuyuan Fu, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Kehang Han, Karol Hausman, Alexander Herzog, Jasmine Hsu, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Lisa Lee, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Henryk Michalewski, Igor Mordatch, Karl Pertsch, Kanishka Rao, Krista Reymann, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Pierre Sermanet, Jaspiar Singh, Anikait Singh, Radu Soricut, Huong T. Tran, Vincent Vanhoucke, Quan Vuong, Ayzaan Wahid, Stefan Welker, Paul Wohlhart, Jialin Wu, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich
2023 — conf
Scaling Robot Learning with Semantically Imagined Experience.
Robotics: Science and Systems
Tianhe Yu, Ted Xiao, Jonathan Tompson, Austin Stone, Su Wang, Anthony Brohan, Jaspiar Singh, Clayton Tan, Dee M, Jodilyn Peralta, Karol Hausman, Brian Ichter, Fei Xia
2023 J jnl
Scaling Robot Learning with Semantically Imagined Experience.
CoRR
Tianhe Yu, Ted Xiao, Austin Stone, Jonathan Tompson, Anthony Brohan, Su Wang, Jaspiar Singh, Clayton Tan, Dee M, Jodilyn Peralta, Brian Ichter, Karol Hausman, Fei Xia
2023 A* conf
Train Offline, Test Online: A Real Robot Learning Benchmark.
ICRA
Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
2023 J jnl
Train Offline, Test Online: A Real Robot Learning Benchmark.
CoRR
Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
2023 J jnl
Video Language Planning.
CoRR
Yilun Du, Mengjiao Yang, Pete Florence, Fei Xia, Ayzaan Wahid, Brian Ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Andy Zeng, Jonathan Tompson
2023 J jnl
What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?
CoRR
Kaylee Burns, Zach Witzel, Jubayer Ibn Hamid, Tianhe Yu, Chelsea Finn, Karol Hausman
2022 A* conf
How to Leverage Unlabeled Data in Offline Reinforcement Learning.
ICML
Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine
2022 J jnl
How to Leverage Unlabeled Data in Offline Reinforcement Learning.
CoRR
Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine
2022 A* conf
LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning.
NeurIPS
Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Jianhao Wang, Alex Yuan Gao, Wenzhe Li, Liang Bin, Chelsea Finn, Chongjie Zhang
2022 J jnl
Latent-Variable Advantage-Weighted Policy Optimization for Offline RL.
CoRR
Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Yuan Gao, Jianhao Wang, Wenzhe Li, Bin Liang, Chelsea Finn, Chongjie Zhang
2022 Misc conf
Offline Reinforcement Learning at Multiple Frequencies.
CoRL
Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman
2022 J jnl
Offline Reinforcement Learning at Multiple Frequencies.
CoRR
Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman
2022 J jnl
RT-1: Robotics Transformer for Real-World Control at Scale.
CoRR
Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich
2022 J jnl
Single image dehazing based on multi-scale segmentation and deep learning.
Mach. Vis. Appl.
Tianhe Yu, Ming Zhu, Haiming Chen
2021 J jnl
Adaptive superpixel-based multi-object pedestrian recognition.
Mach. Vis. Appl.
Tianhe Yu, Chengdong Wang, Xiao Liu, Ming Zhu
2021 A* conf
COMBO: Conservative Offline Model-Based Policy Optimization.
NeurIPS
Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn
2021 J jnl
COMBO: Conservative Offline Model-Based Policy Optimization.
CoRR
Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn
2021 A* conf
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning.
NeurIPS
Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn
2021 J jnl
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning.
CoRR
Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn
2021 A* conf
Efficiently Identifying Task Groupings for Multi-Task Learning.
NeurIPS
Chris Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
2021 J jnl
Efficiently Identifying Task Groupings for Multi-Task Learning.
CoRR
Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
2021 J jnl
Image Enhancement Algorithm Based on Image Spatial Domain Segmentation.
Comput. Informatics
Tianhe Yu, Ming Zhu
2021 — conf
Offline Reinforcement Learning from Images with Latent Space Models.
L4DC
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
2021 A* conf
Visual Adversarial Imitation Learning using Variational Models.
NeurIPS
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
2021 J jnl
Visual Adversarial Imitation Learning using Variational Models.
CoRR
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
2020 A* conf
Gradient Surgery for Multi-Task Learning.
NeurIPS
Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
2020 J jnl
Gradient Surgery for Multi-Task Learning.
CoRR
Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
2020 A* conf
MOPO: Model-based Offline Policy Optimization.
NeurIPS
Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma
2020 J jnl
MOPO: Model-based Offline Policy Optimization.
CoRR
Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma
2020 J jnl
Measuring and Harnessing Transference in Multi-Task Learning.
CoRR
Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
2020 J jnl
Offline Reinforcement Learning from Images with Latent Space Models.
CoRR
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
2020 A* conf
On the Expressivity of Neural Networks for Deep Reinforcement Learning.
ICML
Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma
2020 J jnl
Variable-Shot Adaptation for Online Meta-Learning.
CoRR
Tianhe Yu, Xinyang Geng, Chelsea Finn, Sergey Levine
2019 A* conf
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables.
NeurIPS
Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon
2019 J jnl
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables.
CoRR
Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon
2019 Misc conf
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning.
CoRL
Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, Sergey Levine
2019 J jnl
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning.
CoRR
Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, Sergey Levine
2019 A conf
One-Shot Composition of Vision-Based Skills from Demonstration.
IROS
Tianhe Yu, Pieter Abbeel, Sergey Levine, Chelsea Finn
2019 — conf
Unsupervised Visuomotor Control through Distributional Planning Networks.
Robotics: Science and Systems
Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn
2019 J jnl
Unsupervised Visuomotor Control through Distributional Planning Networks.
CoRR
Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn
2018 J jnl
One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks.
CoRR
Tianhe Yu, Pieter Abbeel, Sergey Levine, Chelsea Finn
2018 — conf
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning.
ICLR (Workshop)
Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2018 — conf
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning.
Robotics: Science and Systems
Tianhe Yu, Chelsea Finn, Sudeep Dasari, Annie Xie, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2018 J jnl
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning.
CoRR
Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2018 Misc conf
SMEM++: A Pipelined and Time-Multiplexed SMEM Seeding Accelerator for DNA Sequencing.
FCCM
Jason Cong, Licheng Guo, Po-Tsang Huang, Peng Wei, Tianhe Yu
2018 B conf
SMEM++: A Pipelined and Time-Multiplexed SMEM Seeding Accelerator for Genome Sequencing.
FPL
Jason Cong, Licheng Guo, Po-Tsang Huang, Peng Wei, Tianhe Yu
2018 — —
SMEM++: A Pipelined and Time-Multiplexed SMEM Seeding Accelerator for Genome Sequencing.
Tianhe Yu
2017 — conf
Generalizing Skills with Semi-Supervised Reinforcement Learning.
ICLR (Poster)
Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine
2017 Misc conf
One-Shot Visual Imitation Learning via Meta-Learning.
CoRL
Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2017 J jnl
One-Shot Visual Imitation Learning via Meta-Learning.
CoRR
Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine
2017 J jnl
Real-Time User-Guided Image Colorization with Learned Deep Priors.
CoRR
Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros
2017 J jnl
Real-time user-guided image colorization with learned deep priors.
ACM Trans. Graph.
Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros
2016 — conf
Calibration Method to the Temperature Measuring System Based on Color CCD Camera.
IGTA
Tianhe Yu, Yongjin Zhang, Jingmin Dai
2016 J jnl
Generalizing Skills with Semi-Supervised Reinforcement Learning.
CoRR
Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine