Objective quality assessment of multiply distorted images. - Dinesh Jayaraman; Anish Mittal; Anush K. Moorthy; Alan C. Bovik (ACSCC, 2012)

Decorrelating Semantic Visual Attributes by Resisting the Urge to Share. - Dinesh Jayaraman; Fei Sha; Kristen Grauman (CVPR, 2014)

Zero-shot recognition with unreliable attributes. - Dinesh Jayaraman; Kristen Grauman (NIPS, 2014)

Learning Image Representations Tied to Ego-Motion. - Dinesh Jayaraman; Kristen Grauman (ICCV, 2015)

Learning image representations equivariant to ego-motion. - Dinesh Jayaraman; Kristen Grauman (CoRR, 2015)

Object-Centric Representation Learning from Unlabeled Videos. - Ruohan Gao; Dinesh Jayaraman; Kristen Grauman (ACCV (5), 2016)

Slow and Steady Feature Analysis: Higher Order Temporal Coherence in Video. - Dinesh Jayaraman; Kristen Grauman (CVPR, 2016)

Look-Ahead Before You Leap: End-to-End Active Recognition by Forecasting the Effect of Motion. - Dinesh Jayaraman; Kristen Grauman (ECCV (5), 2016)

Pano2Vid: Automatic Cinematography for Watching 360° Videos. - Yu-Chuan Su; Dinesh Jayaraman; Kristen Grauman (WICED@Eurographics, 2017)

Unsupervised learning through one-shot image-based shape reconstruction. - Dinesh Jayaraman; Ruohan Gao; Kristen Grauman (CoRR, 2017)

Learning to look around. - Dinesh Jayaraman; Kristen Grauman (CoRR, 2017)

Learning Image Representations Tied to Egomotion from Unlabeled Video. - Dinesh Jayaraman; Kristen Grauman (Int. J. Comput. Vis., 2017)

Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks. - Dinesh Jayaraman; Kristen Grauman (CVPR, 2018)

ShapeCodes: Self-supervised Feature Learning by Lifting Views to Viewgrids. - Dinesh Jayaraman; Ruohan Gao; Kristen Grauman (ECCV (16), 2018)

More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch. - Roberto Calandra; Andrew Owens; Dinesh Jayaraman; Justin Lin; Wenzhen Yuan 001; Jitendra Malik; Edward H. Adelson; Sergey Levine (IEEE Robotics Autom. Lett., 2018)

Time-Agnostic Prediction: Predicting Predictable Video Frames. - Dinesh Jayaraman; Frederik Ebert; Alexei A. Efros; Sergey Levine (ICLR (Poster), 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 (ICRA, 2019)

REPLAB: A Reproducible Low-Cost Arm Benchmark for Robotic Learning. - Brian H. Yang; Dinesh Jayaraman; Jesse Zhang; Sergey Levine (ICRA, 2019)

Causal Confusion in Imitation Learning. - Pim de Haan; Dinesh Jayaraman; Sergey Levine (NeurIPS, 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)

SMiRL: Surprise Minimizing RL in Dynamic Environments. - Glen Berseth; Daniel Geng; Coline Devin; Chelsea Finn; Dinesh Jayaraman; Sergey Levine (CoRR, 2019)

End-to-End Policy Learning for Active Visual Categorization. - Dinesh Jayaraman; Kristen Grauman (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Emergence of exploratory look-around behaviors through active observation completion. - Santhosh K. Ramakrishnan; Dinesh Jayaraman; Kristen Grauman (Sci. Robotics, 2019)

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

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

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. - Karl Pertsch; Oleh Rybkin; Frederik Ebert; Shenghao Zhou; Dinesh Jayaraman; Chelsea Finn; Sergey Levine (NeurIPS, 2020)

Fighting Copycat Agents in Behavioral Cloning from Observation Histories. - Chuan Wen; Jierui Lin; Trevor Darrell; Dinesh Jayaraman; Yang Gao 029 (NeurIPS, 2020)

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors. - Karl Pertsch; Oleh Rybkin; Frederik Ebert; Chelsea Finn; Dinesh Jayaraman; Sergey Levine (CoRR, 2020)

Diverse Sampling for Normalizing Flow Based Trajectory Forecasting. - Yecheng Jason Ma; Jeevana Priya Inala; Dinesh Jayaraman; Osbert Bastani (CoRR, 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)

Morphology-Agnostic Visual Robotic Control. - Brian H. Yang; Dinesh Jayaraman; Glen Berseth; Alexei A. Efros; Sergey Levine (IEEE Robotics Autom. Lett., 2020)

Probabilistic Modeling for Human Mesh Recovery. - Nikos Kolotouros; Georgios Pavlakos; Dinesh Jayaraman; Kostas Daniilidis (ICCV, 2021)

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

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments. - Glen Berseth; Daniel Geng; Coline Manon Devin; Nicholas Rhinehart; Chelsea Finn; Dinesh Jayaraman; Sergey Levine (ICLR, 2021)

Keyframe-Focused Visual Imitation Learning. - Chuan Wen; Jierui Lin; Jianing Qian; Yang Gao 029; Dinesh Jayaraman (ICML, 2021)

How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control? - Jingxi Xu 002; Bruce D. Lee; Nikolai Matni; Dinesh Jayaraman (L4DC, 2021)

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

Know Thyself: Transferable Visuomotor Control Through Robot-Awareness. - Edward S. Hu; Kun Huang; Oleh Rybkin; Dinesh Jayaraman (CoRR, 2021)

An Exploration of Embodied Visual Exploration. - Santhosh K. Ramakrishnan; Dinesh Jayaraman; Kristen Grauman (Int. J. Comput. Vis., 2021)

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

Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning. - Kun Huang; Edward S. Hu; Dinesh Jayaraman (CoRL, 2022)

Discovering Deformable Keypoint Pyramids. - Jianing Qian; Anastasios Panagopoulos; Dinesh Jayaraman (ECCV (26), 2022)

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

Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching. - Yecheng Jason Ma; Andrew Shen; Dinesh Jayaraman; Osbert Bastani (ICML, 2022)

Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming. - Chuan Wen; Jianing Qian; Jierui Lin; Jiaye Teng; Dinesh Jayaraman; Yang Gao 029 (ICML, 2022)

Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression. - Yecheng Jason Ma; Jason Yan; Dinesh Jayaraman; Osbert Bastani (NeurIPS, 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; et al. (CoRR, 2022)

SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching. - Yecheng Jason Ma; Andrew Shen; Dinesh Jayaraman; Osbert Bastani (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)

Vision-based Perimeter Defense via Multiview Pose Estimation. - Elijah S. Lee; Giuseppe Loianno; Dinesh Jayaraman; Vijay Kumar 001 (CoRR, 2022)

Prospective Learning: Principled Extrapolation to the Future. - Ashwin De Silva; Rahul Ramesh; Lyle H. Ungar; Marshall G. Hussain Shuler; Noah J. Cowan; Michael L. Platt; Chen Li; Leyla Isik; Seung-Eon Roh; Adam S. Charles; Archana Venkataraman; Brian Caffo; et al. (CoLLAs, 2023)

Im2Contact: Vision-Based Contact Localization Without Touch or Force Sensing. - Leon Kim; Yunshuang Li; Michael Posa; Dinesh Jayaraman (CoRL, 2023)

Planning Goals for Exploration. - Edward S. Hu; Richard Chang; Oleh Rybkin; Dinesh Jayaraman (ICLR, 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 001 (ICLR, 2023)

LIV: Language-Image Representations and Rewards for Robotic Control. - Yecheng Jason Ma; Vikash Kumar; Amy Zhang 001; Osbert Bastani; Dinesh Jayaraman (ICML, 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 (L4DC, 2023)

Learning a Meta-Controller for Dynamic Grasping. - Yinsen Jia; Jingxi Xu 002; Dinesh Jayaraman; Shuran Song (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)

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)

LIV: Language-Image Representations and Rewards for Robotic Control. - Yecheng Jason Ma; William Liang; Vaidehi Som; Vikash Kumar; Amy Zhang 001; Osbert Bastani; Dinesh Jayaraman (CoRR, 2023)

DiffusionPhase: Motion Diffusion in Frequency Domain. - Weilin Wan 001; Yiming Huang; Shutong Wu; Taku Komura; Wenping Wang 001; Dinesh Jayaraman; Lingjie Liu (CoRR, 2023)

Dynamic Grasping with a Learned Meta-Controller. - Yinsen Jia; Jingxi Xu 002; Dinesh Jayaraman; Shuran Song (CASE, 2024)

Environment Curriculum Generation via Large Language Models. - William Liang; Sam Wang; Hung-Ju Wang; Osbert Bastani; Dinesh Jayaraman; Yecheng Jason Ma (CoRL, 2024)

Task-Oriented Hierarchical Object Decomposition for Visuomotor Control. - Jianing Qian; Yunshuang Li; Bernadette Bucher; Dinesh Jayaraman (CoRL, 2024)

TLControl: Trajectory and Language Control for Human Motion Synthesis. - Weilin Wan 001; Zhiyang Dou; Taku Komura; Wenping Wang 001; Dinesh Jayaraman; Lingjie Liu (ECCV (37), 2024)

Privileged Sensing Scaffolds Reinforcement Learning. - Edward S. Hu; James Springer; Oleh Rybkin; Dinesh Jayaraman (ICLR, 2024)

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 (ICLR, 2024)

Memory-Consistent Neural Networks for Imitation Learning. - Kaustubh Sridhar; Souradeep Dutta; Dinesh Jayaraman; James Weimer; Insup Lee 001 (ICLR, 2024)

ZeroFlow: Scalable Scene Flow via Distillation. - Kyle Vedder; Neehar Peri; Nathaniel Chodosh; Ishan Khatri; Eric Eaton; Dinesh Jayaraman; Yang Liu; Deva Ramanan; James Hays (ICLR, 2024)

Can Transformers Capture Spatial Relations between Objects? - Chuan Wen; Dinesh Jayaraman; Yang Gao 029 (ICLR, 2024)

Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. - Zichen Zhang 016; Yunshuang Li; Osbert Bastani; Abhishek Gupta 004; Dinesh Jayaraman; Yecheng Jason Ma; Luca Weihs (ICRA, 2024)

Long-HOT: A Modular Hierarchical Approach for Long-Horizon Object Transport. - Sriram Narayanan; Dinesh Jayaraman; Manmohan Chandraker (ICRA, 2024)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 2024)

Recasting Generic Pretrained Vision Transformers As Object-Centric Scene Encoders For Manipulation Policies. - Jianing Qian; Anastasios Panagopoulos; Dinesh Jayaraman (ICRA, 2024)

Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models. - Junyao Shi; Jianing Qian; Yecheng Jason Ma; Dinesh Jayaraman (ICRA, 2024)

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. - Alexander Khazatsky; Karl Pertsch; Suraj Nair 003; Ashwin Balakrishna; Sudeep Dasari; Siddharth Karamcheti; Soroush Nasiriany; Mohan Kumar Srirama; Lawrence Yunliang Chen; Kirsty Ellis; Peter David Fagan; Joey Hejna; et al. (Robotics: Science and Systems, 2024)

DrEureka: Language Model Guided Sim-To-Real Transfer. - Yecheng Jason Ma; William Liang; Hung-Ju Wang; Yuke Zhu; Linxi Fan; Osbert Bastani; Dinesh Jayaraman (Robotics: Science and Systems, 2024)

DrEureka: Language Model Guided Sim-To-Real Transfer. - Yecheng Jason Ma; William Liang; Hung-Ju Wang; Sam Wang; Yuke Zhu; Linxi Fan; Osbert Bastani; Dinesh Jayaraman (CoRR, 2024)

Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systems. - Jake Welde; Nishanth Rao; Pratik Kunapuli; Dinesh Jayaraman; Vijay Kumar 001 (CoRR, 2024)

Learning to Achieve Goals with Belief State Transformers. - Edward S. Hu; Kwangjun Ahn; Qinghua Liu; Haoran Xu; Manan Tomar; Ada Langford; Dinesh Jayaraman; Alex Lamb; John Langford 001 (CoRR, 2024)

Eurekaverse: Environment Curriculum Generation via Large Language Models. - William Liang; Sam Wang; Hung-Ju Wang; Osbert Bastani; Dinesh Jayaraman; Yecheng Jason Ma (CoRR, 2024)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma; Joey Hejna; Ayzaan Wahid; Chuyuan Fu; Dhruv Shah; Jacky Liang; Zhuo Xu; Sean Kirmani; Peng Xu 010; Danny Driess; Ted Xiao; Jonathan Tompson; et al. (CoRR, 2024)

The Belief State Transformer. - Edward S. Hu; Kwangjun Ahn; Qinghua Liu; Haoran Xu; Manan Tomar; Ada Langford; Dinesh Jayaraman; Alex Lamb; John Langford 001 (ICLR, 2025)

The Value of Sensory Information to a Robot. - Arjun Krishna; Edward S. Hu; Dinesh Jayaraman (ICLR, 2025)

Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model. - Long Le; Jason Xie; William Liang; Hung-Ju Wang; Yue Yang; Yecheng Jason Ma; Kyle Vedder; Arjun Krishna; Dinesh Jayaraman; Eric Eaton (ICLR, 2025)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma; Joey Hejna; Chuyuan Fu; Dhruv Shah; Jacky Liang; Zhuo Xu; Sean Kirmani; Peng Xu 010; Danny Driess; Ted Xiao; Osbert Bastani; Dinesh Jayaraman; et al. (ICLR, 2025)

REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments. - Kaustubh Sridhar; Souradeep Dutta; Dinesh Jayaraman; Insup Lee 001 (ICLR, 2025)

Illustrated Landmark Graphs for Long-horizon Policy Learning. - Christopher Watson; Arjun Krishna; Rajeev Alur; Dinesh Jayaraman (Trans. Mach. Learn. Res., 2025)

ZeroMimic: Distilling Robotic Manipulation Skills from Web Videos. - Junyao Shi; Zhuolun Zhao; Tianyou Wang; Ian Pedroza; Amy Luo; Jie Wang; Jason Ma; Dinesh Jayaraman (CoRR, 2025)

Leveling the Playing Field: Carefully Comparing Classical and Learned Controllers for Quadrotor Trajectory Tracking. - Pratik Kunapuli; Jake Welde; Dinesh Jayaraman; Vijay Kumar 001 (CoRR, 2025)

RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies. - Pranav Atreya; Karl Pertsch; Tony Lee; Moo Jin Kim; Arhan Jain; Artur Kuramshin; Clemens Eppner; Cyrus Neary; Edward S. Hu; Fabio Ramos 001; Jonathan Tremblay; Kanav Arora; et al. (CoRR, 2025)

VLMgineer: Vision Language Models as Robotic Toolsmiths. - George Jiayuan Gao; Tianyu Li; Junyao Shi; Yihan Li; Zizhe Zhang; Nadia Figueroa; Dinesh Jayaraman (CoRR, 2025)

RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models. - Kaustubh Sridhar; Souradeep Dutta; Dinesh Jayaraman; Insup Lee 001 (CoRR, 2025)