Dinesh Jayaraman

Ashwin De Silva, Rahul Ramesh, Lyle Ungar, Marshall Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu Timothy Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein (2023). Prospective Learning: Principled Extrapolation to the Future. Proceedings of The 2nd Conference on Lifelong Learning Agents.

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Leon Kim, Yunshuang Li, Michael Posa, Dinesh Jayaraman (2023). Vision-Based Contact Localization Without Touch or Force Sensing. CORL.

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Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman (2023). LIV: Language-Image Representations and Rewards for Robotic Control. ICML.

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Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang (2023). VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. ICLR (top 25%).

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Edward Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman (2023). Planning Goals for Exploration. ICLR (top 25 per cent) and CORL 2022 Robot Adaptation Workshop Best Paper Award.

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Yecheng Jason Ma, Kausik Sivakumar, Jason Yen, Osbert Bastani, Dinesh Jayaraman (2023). Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. L4DC.

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Yinsen Jia, Jingxi Xu, Dinesh Jayaraman, Shuran Song (2023). Learning a Meta-Controller for Dynamic Grasping. arXiv preprint arXiv:2302.08463.

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Kun Huang, Edward Hu, Dinesh Jayaraman (2022). Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning. CORL (best paper award).

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Jianing Qian, Anastasios Panagopoulos, Dinesh Jayaraman (2022). Discovering Deformable Keypoint Pyramids. ECCV.

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Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani (2022). How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via $ f $-Advantage Regression. NeurIPS.

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Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani (2022). SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching. In ICML.

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Chuan Wen, Jianing Qian, Jierui Lin, Jiaye Teng, Dinesh Jayaraman, Yang Gao (2022). Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming. ICML.

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Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman (2022). Know Thyself: Transferable Visuomotor Control Through Robot-Awareness. In ICLR.

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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 (2022). Prospective Learning: Back to the Future. In arXiv.

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Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman (2022). Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning. AAAI.

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Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman (2021). Keyframe-Focused Visual Imitation Learning. In ICML.

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Hui Chen, Zhao Li, Sheng Feng, Anni Wang, Melissa Richard-Greenblatt, Emily Hutson, Stefen Andrianus, Laurel J. Glaser, Kyle G. Rodino, Jianing Qian, Dinesh Jayaraman, Ronald G. Collman, Abigail Glascock, Frederic D. Bushman, Jae Seung Lee, Sara Cherry, Alejandra Fausto, Susan R. Weiss, Hyun Koo, Patricia M. Corby, Una O'Doherty, Alfred L. Garfall, Dan T. Vogl, Edward A. Stadtmauer, Ping Wang (2021). Femtomolar SARS-CoV-2 Antigen Detection Using the Microbubbling Digital Assay with Smartphone Readout Enables Antigen Burden Quantitation and Dynamics Tracking. Clinical Chemistry.

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Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani (2021). Likelihood-Based Diverse Sampling for Trajectory Forecasting. ICCV.

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Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani (2021). Conservative Offline Distributional Reinforcement Learning. In NeurIPS.

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Jingxi Xu, Bruce Lee, Nikolai Matni, Dinesh Jayaraman (2021). How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?. L4DC.

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Santhosh K Ramakrishnan, Dinesh Jayaraman, Kristen Grauman (2021). An Exploration of Embodied Visual Exploration. In IJCV.

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Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine (2021). SMIRL: Surprise Minimizing RL in Dynamic Environments. In ICLR.

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Jianing Qian, Dinesh Jayaraman (2021). Object Representations Guided By Optical Flow. NeurIPS Robot Learning Workshop.

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Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, Kostas Daniilidis (2021). Embracing the Reconstruction Uncertainty in 3D Human Pose Estimation. ICCV.

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Neha Das, Sarah Bechtle, Todor Davchev, Dinesh Jayaraman, Akshara Rai, Franziska Meier (2020). Model-Based Inverse Reinforcement Learning from Visual Demonstrations. In CORL.

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Chuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, Yang Gao (2020). Fighting Copycat Agents in Behavioral Cloning from Multiple Observations.. In NeurIPS.

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Karl Pertsch*, Oleg Rybkin*, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine (2020). Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. In NeurIPS.

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Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman (2020). Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. ICML.

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Brian Yang*, Dinesh Jayaraman*, Glen Berseth, Alexei Efros, Sergey Levine (2020). MAVRIC: Morphology-Agnostic Visual Robotic Control. In ICRA and RA-L.

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Mike Lambeta, Po-Wei Chou, Stephen Tian, Brian Yang, Benjamin Maloon, Victoria Rose Most, Dave Stroud, Raymond Santos, Ahmad Byagowi, Gregg Kammerer, Dinesh Jayaraman, Roberto Calandra (2020). DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation. In ICRA and RA-L.

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