Dinesh Jayaraman

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 100

Top Venues

Publications

Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, James Weimer, Insup Lee
Memory-Consistent Neural Networks for Imitation Learning. ICLR (2024)
Chuan Wen, Dinesh Jayaraman, Yang Gao
Can Transformers Capture Spatial Relations between Objects? CoRR (2024)
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 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 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, 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
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA (2024)
Sriram Narayanan, Dinesh Jayaraman, Manmohan Chandraker
Long-HOT: A Modular Hierarchical Approach for Long-Horizon Object Transport. ICRA (2024)
Junyao Shi, Jianing Qian, Yecheng Jason Ma, Dinesh Jayaraman
Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models. CoRR (2024)
Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays
ZeroFlow: Scalable Scene Flow via Distillation. ICLR (2024)
Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. ICRA (2024)
Junyao Shi, Jianing Qian, Yecheng Jason Ma, Dinesh Jayaraman
Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models. ICRA (2024)
Yecheng Jason Ma, William Liang, Hung-Ju Wang, Sam Wang, Yuke Zhu, Linxi Fan, Osbert Bastani, Dinesh Jayaraman
DrEureka: Language Model Guided Sim-To-Real Transfer. CoRR (2024)
Jianing Qian, Anastasios Panagopoulos, Dinesh Jayaraman
Recasting Generic Pretrained Vision Transformers As Object-Centric Scene Encoders For Manipulation Policies. ICRA (2024)
Edward S. Hu, James Springer, Oleh Rybkin, Dinesh Jayaraman
Privileged Sensing Scaffolds Reinforcement Learning. ICLR (2024)
Edward S. Hu, James Springer, Oleh Rybkin, Dinesh Jayaraman
Privileged Sensing Scaffolds Reinforcement Learning. CoRR (2024)
Jianing Qian, Anastasios Panagopoulos, Dinesh Jayaraman
Recasting Generic Pretrained Vision Transformers As Object-Centric Scene Encoders For Manipulation Policies. CoRR (2024)
Chuan Wen, Dinesh Jayaraman, Yang Gao
Can Transformers Capture Spatial Relations between Objects? ICLR (2024)
Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar
Eureka: Human-Level Reward Design via Coding Large Language Models. ICLR (2024)
Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays
ZeroFlow: Fast Zero Label Scene Flow via Distillation. CoRR (2023)
Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman
TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. CoRR (2023)
Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar
Eureka: Human-Level Reward Design via Coding Large Language Models. CoRR (2023)
Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman
Planning Goals for Exploration. ICLR (2023)
Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman
Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. L4DC (2023)
Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman
Planning Goals for Exploration. CoRR (2023)
Weilin Wan, Yiming Huang, Shutong Wu, Taku Komura, Wenping Wang, Dinesh Jayaraman, Lingjie Liu
DiffusionPhase: Motion Diffusion in Frequency Domain. CoRR (2023)
Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. ICLR (2023)
Weilin Wan, Zhiyang Dou, Taku Komura, Wenping Wang, Dinesh Jayaraman, Lingjie Liu
TLControl: Trajectory and Language Control for Human Motion Synthesis. CoRR (2023)
Yinsen Jia, Jingxi Xu, Dinesh Jayaraman, Shuran Song
Learning a Meta-Controller for Dynamic Grasping. CoRR (2023)
Yecheng Jason Ma, William Liang, Vaidehi Som, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman
LIV: Language-Image Representations and Rewards for Robotic Control. CoRR (2023)
Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. CoRR (2023)
Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman
LIV: Language-Image Representations and Rewards for Robotic Control. ICML (2023)
Leon Kim, Yunshuang Li, Michael Posa, Dinesh Jayaraman
Im2Contact: Vision-Based Contact Localization Without Touch or Force Sensing. CoRL (2023)
Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. 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 C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
Prospective Learning: Principled Extrapolation to the Future. CoLLAs (2023)
Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, James Weimer, Insup Lee
Memory-Consistent Neural Networks for Imitation Learning. CoRR (2023)
Jianing Qian, Anastasios Panagopoulos, Dinesh Jayaraman
Discovering Deformable Keypoint Pyramids. ECCV (26) (2022)
Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani
How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression. CoRR (2022)
Sriram Narayanan, Dinesh Jayaraman, Manmohan Chandraker
Long-HOT: A Modular Hierarchical Approach for Long-Horizon Object Transport. CoRR (2022)
Kun Huang, Edward S. Hu, Dinesh Jayaraman
Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning. CoRL (2022)
Elijah S. Lee, Giuseppe Loianno, Dinesh Jayaraman, Vijay Kumar
Vision-based Perimeter Defense via Multiview Pose Estimation. CoRR (2022)
Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning. AAAI (2022)
Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman
Know Thyself: Transferable Visual Control Policies Through Robot-Awareness. ICLR (2022)
Chuan Wen, Jianing Qian, Jierui Lin, Jiaye Teng, Dinesh Jayaraman, Yang Gao
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming. CoRR (2022)
Kun Huang, Edward S. Hu, Dinesh Jayaraman
Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning. CoRR (2022)
Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani
Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression. NeurIPS (2022)
Chuan Wen, Jianing Qian, Jierui Lin, Jiaye Teng, Dinesh Jayaraman, Yang Gao
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming. ICML (2022)
Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. CoRR (2022)
Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani
SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching. CoRR (2022)
Joshua T. Vogelstein, Timothy Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. 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, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
Prospective Learning: Back to the Future. CoRR (2022)
Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani
Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching. ICML (2022)
Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning. CoRR (2021)
Jingxi Xu, Bruce Lee, Nikolai Matni, Dinesh Jayaraman
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control? CoRR (2021)
Jingxi Xu, Bruce Lee, Nikolai Matni, Dinesh Jayaraman
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control? L4DC (2021)
Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman
An Exploration of Embodied Visual Exploration. Int. J. Comput. Vis. 129 (5) (2021)
Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani
Conservative Offline Distributional Reinforcement Learning. NeurIPS (2021)
Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman
Keyframe-Focused Visual Imitation Learning. CoRR (2021)
Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, Kostas Daniilidis
Probabilistic Modeling for Human Mesh Recovery. ICCV (2021)
Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman
Know Thyself: Transferable Visuomotor Control Through Robot-Awareness. CoRR (2021)
Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani
Likelihood-Based Diverse Sampling for Trajectory Forecasting. ICCV (2021)
Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments. ICLR (2021)
Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman
Keyframe-Focused Visual Imitation Learning. ICML (2021)
Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, Kostas Daniilidis
Probabilistic Modeling for Human Mesh Recovery. CoRR (2021)
Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani
Conservative Offline Distributional Reinforcement Learning. CoRR (2021)
Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. ICML (2020)
Mike Lambeta, Po-Wei Chou, Stephen Tian, Brian H. Yang, Benjamin Maloon, Victoria Rose Most, Dave Stroud, Raymond Santos, Ahmad Byagowi, Gregg Kammerer, Dinesh Jayaraman, Roberto Calandra
DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor With Application to In-Hand Manipulation. IEEE Robotics Autom. Lett. 5 (3) (2020)
Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. CoRR (2020)
Brian H. Yang, Dinesh Jayaraman, Glen Berseth, Alexei A. Efros, Sergey Levine
Morphology-Agnostic Visual Robotic Control. IEEE Robotics Autom. Lett. 5 (2) (2020)
Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman
An Exploration of Embodied Visual Exploration. CoRR (2020)
Karl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. NeurIPS (2020)
Chuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, Yang Gao
Fighting Copycat Agents in Behavioral Cloning from Observation Histories. CoRR (2020)
Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings. CoRR (2020)
Neha Das, Sarah Bechtle, Todor Davchev, Dinesh Jayaraman, Akshara Rai, Franziska Meier
Model-Based Inverse Reinforcement Learning from Visual Demonstrations. CoRR (2020)
Mike Lambeta, Po-Wei Chou, Stephen Tian, Brian H. Yang, Benjamin Maloon, Victoria Rose Most, Dave Stroud, Raymond Santos, Ahmad Byagowi, Gregg Kammerer, Dinesh Jayaraman, Roberto Calandra
DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation. CoRR (2020)
Chuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, Yang Gao
Fighting Copycat Agents in Behavioral Cloning from Observation Histories. NeurIPS (2020)
Neha Das, Sarah Bechtle, Todor Davchev, Dinesh Jayaraman, Akshara Rai, Franziska Meier
Model-Based Inverse Reinforcement Learning from Visual Demonstrations. CoRL (2020)
Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani
Diverse Sampling for Normalizing Flow Based Trajectory Forecasting. CoRR (2020)
Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine
Manipulation by Feel: Touch-Based Control with Deep Predictive Models. CoRR (2019)
Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
SMiRL: Surprise Minimizing RL in Dynamic Environments. CoRR (2019)
Pim de Haan, Dinesh Jayaraman, Sergey Levine
Causal Confusion in Imitation Learning. NeurIPS (2019)
Brian H. Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, Dinesh Jayaraman
REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning. CoRR (2019)
Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine
Manipulation by Feel: Touch-Based Control with Deep Predictive Models. ICRA (2019)
Brian H. Yang, Dinesh Jayaraman, Glen Berseth, Alexei A. Efros, Sergey Levine
Morphology-Agnostic Visual Robotic Control. CoRR (2019)
Brian H. Yang, Dinesh Jayaraman, Jesse Zhang, Sergey Levine
REPLAB: A Reproducible Low-Cost Arm Benchmark for Robotic Learning. ICRA (2019)
Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros, Sergey Levine
Time-Agnostic Prediction: Predicting Predictable Video Frames. ICLR (Poster) (2019)
Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman
Emergence of Exploratory Look-Around Behaviors through Active Observation Completion. CoRR (2019)
Pim de Haan, Dinesh Jayaraman, Sergey Levine
Causal Confusion in Imitation Learning. CoRR (2019)
Dinesh Jayaraman, Kristen Grauman
End-to-End Policy Learning for Active Visual Categorization. IEEE Trans. Pattern Anal. Mach. Intell. 41 (7) (2019)
Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman
Emergence of exploratory look-around behaviors through active observation completion. Sci. Robotics 4 (30) (2019)
Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H. Adelson, Sergey Levine
More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch. IEEE Robotics Autom. Lett. 3 (4) (2018)
Dinesh Jayaraman, Ruohan Gao, Kristen Grauman
ShapeCodes: Self-supervised Feature Learning by Lifting Views to Viewgrids. ECCV (16) (2018)
Dinesh Jayaraman, Kristen Grauman
Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks. CVPR (2018)
Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H. Adelson, Sergey Levine
More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch. CoRR (2018)
Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros, Sergey Levine
Time-Agnostic Prediction: Predicting Predictable Video Frames. CoRR (2018)
Dinesh Jayaraman, Kristen Grauman
Learning Image Representations Tied to Egomotion from Unlabeled Video. Int. J. Comput. Vis. 125 (1-3) (2017)
Dinesh Jayaraman, Ruohan Gao, Kristen Grauman
Unsupervised learning through one-shot image-based shape reconstruction. CoRR (2017)
Dinesh Jayaraman, Kristen Grauman
Learning to look around. CoRR (2017)
Yu-Chuan Su, Dinesh Jayaraman, Kristen Grauman
Pano2Vid: Automatic Cinematography for Watching 360° Videos. WICED@Eurographics (2017)
Ruohan Gao, Dinesh Jayaraman, Kristen Grauman
Object-Centric Representation Learning from Unlabeled Videos. ACCV (5) (2016)
Yu-Chuan Su, Dinesh Jayaraman, Kristen Grauman
Pano2Vid: Automatic Cinematography for Watching 360° Videos. ACCV (4) (2016)
Ruohan Gao, Dinesh Jayaraman, Kristen Grauman
Object-Centric Representation Learning from Unlabeled Videos. CoRR (2016)
Dinesh Jayaraman, Kristen Grauman
Slow and Steady Feature Analysis: Higher Order Temporal Coherence in Video. CVPR (2016)
Dinesh Jayaraman, Kristen Grauman
Look-Ahead Before You Leap: End-to-End Active Recognition by Forecasting the Effect of Motion. ECCV (5) (2016)
Dinesh Jayaraman, Kristen Grauman
Look-ahead before you leap: end-to-end active recognition by forecasting the effect of motion. CoRR (2016)
Yu-Chuan Su, Dinesh Jayaraman, Kristen Grauman
Pano2Vid: Automatic Cinematography for Watching 360° Videos. CoRR (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Dinesh Jayaraman