Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Bohan Wu

Bohan Wu

Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks


Sep 21, 2021
Bohan Wu, Suraj Nair, Li Fei-Fei, Chelsea Finn

Figure 1 for Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks
Figure 2 for Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks
Figure 3 for Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks
Figure 4 for Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks
* Equal advising and contribution for last two authors 
  Access Paper or Ask Questions

On the Opportunities and Risks of Foundation Models


Aug 18, 2021
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Kohd, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

Figure 1 for On the Opportunities and Risks of Foundation Models
Figure 2 for On the Opportunities and Risks of Foundation Models
Figure 3 for On the Opportunities and Risks of Foundation Models
Figure 4 for On the Opportunities and Risks of Foundation Models
* Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) 
  Access Paper or Ask Questions

Semiparametric count data regression for self-reported mental health


Jun 16, 2021
Daniel R. Kowal, Bohan Wu

Figure 1 for Semiparametric count data regression for self-reported mental health
Figure 2 for Semiparametric count data regression for self-reported mental health
Figure 3 for Semiparametric count data regression for self-reported mental health
Figure 4 for Semiparametric count data regression for self-reported mental health

  Access Paper or Ask Questions

Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction


Mar 26, 2021
Bohan Wu, Suraj Nair, Roberto Martin-Martin, Li Fei-Fei, Chelsea Finn

Figure 1 for Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
Figure 2 for Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
Figure 3 for Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
Figure 4 for Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
* Equal advising and contribution for last two authors 
  Access Paper or Ask Questions

SQUIRL: Robust and Efficient Learning from Video Demonstration of Long-Horizon Robotic Manipulation Tasks


Mar 10, 2020
Bohan Wu, Feng Xu, Zhanpeng He, Abhi Gupta, Peter K. Allen

Figure 1 for SQUIRL: Robust and Efficient Learning from Video Demonstration of Long-Horizon Robotic Manipulation Tasks
Figure 2 for SQUIRL: Robust and Efficient Learning from Video Demonstration of Long-Horizon Robotic Manipulation Tasks
Figure 3 for SQUIRL: Robust and Efficient Learning from Video Demonstration of Long-Horizon Robotic Manipulation Tasks
Figure 4 for SQUIRL: Robust and Efficient Learning from Video Demonstration of Long-Horizon Robotic Manipulation Tasks
* 8 pages 
  Access Paper or Ask Questions

MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning


Oct 10, 2019
Bohan Wu, Iretiayo Akinola, Jacob Varley, Peter Allen

Figure 1 for MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning
Figure 2 for MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning
Figure 3 for MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning
Figure 4 for MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning
* Accepted at 3rd Conference on Robot Learning (CoRL 2019). Oral Presentation 
  Access Paper or Ask Questions

Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes


Mar 25, 2019
Bohan Wu, Iretiayo Akinola, Peter K. Allen

Figure 1 for Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes
Figure 2 for Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes
Figure 3 for Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes
Figure 4 for Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes
* 8 pages 
  Access Paper or Ask Questions

Model Primitive Hierarchical Lifelong Reinforcement Learning


Mar 04, 2019
Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer

Figure 1 for Model Primitive Hierarchical Lifelong Reinforcement Learning
Figure 2 for Model Primitive Hierarchical Lifelong Reinforcement Learning
Figure 3 for Model Primitive Hierarchical Lifelong Reinforcement Learning
Figure 4 for Model Primitive Hierarchical Lifelong Reinforcement Learning
* International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019) 
 * 9 pages, 10 figures. Accepted as a full paper at AAMAS 2019 
  Access Paper or Ask Questions