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Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning


Dec 17, 2022
Kun Huang, Edward S. Hu, Dinesh Jayaraman

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* CoRL 2022 

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Long-HOT: A Modular Hierarchical Approach for Long-Horizon Object Transport


Oct 28, 2022
Sriram Narayanan, Dinesh Jayaraman, Manmohan Chandraker

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VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training


Sep 30, 2022
Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang

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* Project website: https://sites.google.com/view/vip-rl 

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Vision-based Perimeter Defense via Multiview Pose Estimation


Sep 25, 2022
Elijah S. Lee, Giuseppe Loianno, Dinesh Jayaraman, Vijay Kumar

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* 7 pages, 10 figures 

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Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming


Jun 22, 2022
Chuan Wen, Jianing Qian, Jierui Lin, Jiaye Teng, Dinesh Jayaraman, Yang Gao

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* 28 pages, 13 figures, ICML2022 

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How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression


Jun 07, 2022
Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani

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* Project website: https://jasonma2016.github.io/GoFAR/ 

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SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching


Feb 04, 2022
Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani

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* Project website: https://sites.google.com/view/smodice/home 

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Prospective Learning: Back to the Future


Jan 19, 2022
Joshua T. Vogelstein, Timothy Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal Burns, Kwame Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena Savonenko, Ian Phillips, Michael I. Miller, Rene Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish Thakor, Justus M Kebschull, Marilyn Albert, Jinchong Xu, Marshall Hussain Shuler, Brian Caffo, Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan, Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael Platt, Lyle Ungar, Leila Wehbe, Adam Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang

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Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning


Dec 14, 2021
Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman

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* AAAI 2022 

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Probabilistic Modeling for Human Mesh Recovery


Aug 26, 2021
Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, Kostas Daniilidis

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* ICCV 2021. Project page: https://www.seas.upenn.edu/~nkolot/projects/prohmr 

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