Dinesh Jayaraman

According to our database, Dinesh Jayaraman authored at least 67 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Can Transformers Capture Spatial Relations between Objects?

Chuan Wen, Dinesh Jayaraman, Yang Gao

CoRR, 2024

2023

DiffusionPhase: Motion Diffusion in Frequency Domain.

Weilin Wan, Yiming Huang, Shutong Wu, Taku Komura, Wenping Wang, Dinesh Jayaraman, Lingjie Liu

CoRR, 2023

TLControl: Trajectory and Language Control for Human Motion Synthesis.

Weilin Wan, Zhiyang Dou, Taku Komura, Wenping Wang, Dinesh Jayaraman, Lingjie Liu

CoRR, 2023

Eureka: Human-Level Reward Design via Coding Large Language Models.

Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar

CoRR, 2023

Universal Visual Decomposer: Long-Horizon Manipulation Made Easy.

Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs

CoRR, 2023

Memory-Consistent Neural Networks for Imitation Learning.

Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, James Weimer, Insup Lee

CoRR, 2023

LIV: Language-Image Representations and Rewards for Robotic Control.

Yecheng Jason Ma, William Liang, Vaidehi Som, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman

CoRR, 2023

TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching.

Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman

CoRR, 2023

ZeroFlow: Fast Zero Label Scene Flow via Distillation.

Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays

CoRR, 2023

Learning a Meta-Controller for Dynamic Grasping.

Yinsen Jia, Jingxi Xu, Dinesh Jayaraman, Shuran Song

CoRR, 2023

Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching.

Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman

Proceedings of the Learning for Dynamics and Control Conference, 2023

LIV: Language-Image Representations and Rewards for Robotic Control.

Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman

Proceedings of the International Conference on Machine Learning, 2023

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

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Planning Goals for Exploration.

Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Im2Contact: Vision-Based Contact Localization Without Touch or Force Sensing.

Leon Kim, Yunshuang Li, Michael Posa, Dinesh Jayaraman

Proceedings of the Conference on Robot Learning, 2023

Prospective Learning: Principled Extrapolation to the Future.

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

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

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

Sriram Narayanan, Dinesh Jayaraman, Manmohan Chandraker

CoRR, 2022

Vision-based Perimeter Defense via Multiview Pose Estimation.

Elijah S. Lee, Giuseppe Loianno, Dinesh Jayaraman, Vijay Kumar

CoRR, 2022

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

Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani

CoRR, 2022

SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching.

Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani

CoRR, 2022

Prospective Learning: Back to the Future.

Joshua T. Vogelstein, Timothy D. 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 H. 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

CoRR, 2022

Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression.

Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming.

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

Proceedings of the International Conference on Machine Learning, 2022

Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching.

Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani

Proceedings of the International Conference on Machine Learning, 2022

Know Thyself: Transferable Visual Control Policies Through Robot-Awareness.

Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Tenth International Conference on Learning Representations, 2022

Discovering Deformable Keypoint Pyramids.

Jianing Qian, Anastasios Panagopoulos, Dinesh Jayaraman

Proceedings of the Computer Vision - ECCV 2022, 2022

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

Kun Huang, Edward S. Hu, Dinesh Jayaraman

Proceedings of the Conference on Robot Learning, 2022

Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning.

Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

An Exploration of Embodied Visual Exploration.

Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman

Int. J. Comput. Vis., 2021

Know Thyself: Transferable Visuomotor Control Through Robot-Awareness.

Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman

CoRR, 2021

Conservative Offline Distributional Reinforcement Learning.

Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?

Jingxi Xu, Bruce D. Lee, Nikolai Matni, Dinesh Jayaraman

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Keyframe-Focused Visual Imitation Learning.

Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman

Proceedings of the 38th International Conference on Machine Learning, 2021

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments.

Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

Likelihood-Based Diverse Sampling for Trajectory Forecasting.

Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Probabilistic Modeling for Human Mesh Recovery.

Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, Kostas Daniilidis

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Morphology-Agnostic Visual Robotic Control.

Brian H. Yang, Dinesh Jayaraman, Glen Berseth, Alexei A. Efros, Sergey Levine

IEEE Robotics Autom. Lett., 2020

DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor With Application to In-Hand Manipulation.

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

IEEE Robotics Autom. Lett., 2020

Diverse Sampling for Normalizing Flow Based Trajectory Forecasting.

Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani

CoRR, 2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.

Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

CoRR, 2020

Fighting Copycat Agents in Behavioral Cloning from Observation Histories.

Chuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, Yang Gao

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.

Karl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings.

Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman

Proceedings of the 37th International Conference on Machine Learning, 2020

Model-Based Inverse Reinforcement Learning from Visual Demonstrations.

Neha Das, Sarah Bechtle, Todor Davchev, Dinesh Jayaraman, Akshara Rai, Franziska Meier

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Emergence of exploratory look-around behaviors through active observation completion.

Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman

Sci. Robotics, 2019

End-to-End Policy Learning for Active Visual Categorization.

Dinesh Jayaraman, Kristen Grauman

IEEE Trans. Pattern Anal. Mach. Intell., 2019

SMiRL: Surprise Minimizing RL in Dynamic Environments.

Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

CoRR, 2019

REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning.

Brian H. Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, Dinesh Jayaraman

CoRR, 2019

Causal Confusion in Imitation Learning.

Pim de Haan, Dinesh Jayaraman, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

REPLAB: A Reproducible Low-Cost Arm Benchmark for Robotic Learning.

Brian H. Yang, Dinesh Jayaraman, Jesse Zhang, Sergey Levine

Proceedings of the International Conference on Robotics and Automation, 2019

Manipulation by Feel: Touch-Based Control with Deep Predictive Models.

Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine

Proceedings of the International Conference on Robotics and Automation, 2019

Time-Agnostic Prediction: Predicting Predictable Video Frames.

Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros, Sergey Levine

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch.

Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H. Adelson, Sergey Levine

IEEE Robotics Autom. Lett., 2018

ShapeCodes: Self-supervised Feature Learning by Lifting Views to Viewgrids.

Dinesh Jayaraman, Ruohan Gao, Kristen Grauman

Proceedings of the Computer Vision - ECCV 2018, 2018

Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Learning Image Representations Tied to Egomotion from Unlabeled Video.

Dinesh Jayaraman, Kristen Grauman

Int. J. Comput. Vis., 2017

Learning to look around.

Dinesh Jayaraman, Kristen Grauman

CoRR, 2017

Unsupervised learning through one-shot image-based shape reconstruction.

Dinesh Jayaraman, Ruohan Gao, Kristen Grauman

CoRR, 2017

Pano2Vid: Automatic Cinematography for Watching 360° Videos.

Yu-Chuan Su, Dinesh Jayaraman, Kristen Grauman

Proceedings of the 6th Workshop on Intelligent Cinematography and Editing, 2017

2016

Look-Ahead Before You Leap: End-to-End Active Recognition by Forecasting the Effect of Motion.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the Computer Vision - ECCV 2016, 2016

Slow and Steady Feature Analysis: Higher Order Temporal Coherence in Video.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Object-Centric Representation Learning from Unlabeled Videos.

Ruohan Gao, Dinesh Jayaraman, Kristen Grauman

Proceedings of the Computer Vision - ACCV 2016, 2016

2015

Learning image representations equivariant to ego-motion.

Dinesh Jayaraman, Kristen Grauman

CoRR, 2015

Learning Image Representations Tied to Ego-Motion.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Zero-shot recognition with unreliable attributes.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Decorrelating Semantic Visual Attributes by Resisting the Urge to Share.

Dinesh Jayaraman, Fei Sha, Kristen Grauman

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2012

Objective quality assessment of multiply distorted images.

Dinesh Jayaraman, Anish Mittal, Anush K. Moorthy, Alan C. Bovik

Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012