Animesh Garg
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
83
Venues
12
Active years
2015–2025
Best venue rank
A*
Where they publish
Papers
83 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | PWM: Policy Learning with Multi-Task World Models. | Ignat Georgiev, Varun Giridhar, Nicklas Hansen, Animesh Garg |
| 2025 | ICLR | EgoSim: Egocentric Exploration in Virtual Worlds with Multi-modal Conditioning. | Wei Yu, Songheng Yin, Steve Easterbrook, Animesh Garg |
| 2025 | ICRA | RoCoDA: Counterfactual Data Augmentation for Data-Efficient Robot Learning from Demonstrations. | Ezra Ameperosa, Jeremy A. Collins, Mrinal Jain, Animesh Garg |
| 2025 | ICRA | CLIMB: Language-Guided Continual Learning for Task Planning with Iterative Model Building. | Walker Byrnes, Miroslav Bogdanovic, Avi Balakirsky, Stephen Balakirsky, Animesh Garg |
| 2025 | ICRA | SuFIA-BC: Generating High Quality Demonstration Data for Visuomotor Policy Learning in Surgical Subtasks. | Masoud Moghani, Nigel Nelson, Mohamed Ghanem, Andres Diaz-Pinto, Kush Hari, Mahdi Azizian, Ken Goldberg, Sean Huver, Animesh Garg |
| 2025 | IROS | ACGD: Visual Multitask Policy Learning with Asymmetric Critic Guided Distillation. | Krishnan Srinivasan, Jie Xu, Henry Ang, Eric Heiden, Dieter Fox, Jeannette Bohg, Animesh Garg |
| 2024 | CoRL | Discovering Robotic Interaction Modes with Discrete Representation Learning. | Liquan Wang, Ankit Goyal, Haoping Xu, Animesh Garg |
| 2024 | CoRL | SPIRE: Synergistic Planning, Imitation, and Reinforcement Learning for Long-Horizon Manipulation. | Zihan Zhou, Animesh Garg, Dieter Fox, Caelan Reed Garrett, Ajay Mandlekar |
| 2024 | ICML | Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation. | Ignat Georgiev, Krishnan Srinivasan, Jie Xu, Eric Heiden, Animesh Garg |
| 2024 | ICRA | Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. | 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 E. 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 Schlkopf, 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 Bchler, 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 T. 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, Joo Silvrio, 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 Snderhauf, 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 Martn-Martn, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante-Gomez, 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 |
| 2024 | IROS | Fast Explicit-Input Assistance for Teleoperation in Clutter. | Nick Walker, Xuning Yang, Animesh Garg, Maya Cakmak, Dieter Fox, Claudia Prez-D'Arpino |
| 2024 | IROS | SuFIA: Language-Guided Augmented Dexterity for Robotic Surgical Assistants. | Masoud Moghani, Lars Doorenbos, William Chung-Ho Panitch, Sean Huver, Mahdi Azizian, Ken Goldberg, Animesh Garg |
| 2024 | ICRA | Orbit-Surgical: An Open-Simulation Framework for Learning Surgical Augmented Dexterity. | Qinxi Yu, Masoud Moghani, Karthik Dharmarajan, Vincent Schorp, William Chung-Ho Panitch, Jingzhou Liu, Kush Hari, Huang Huang, Mayank Mittal, Ken Goldberg, Animesh Garg |
| 2024 | ICRA | HandyPriors: Physically Consistent Perception of Hand-Object Interactions with Differentiable Priors. | Shutong Zhang, Yi-Ling Qiao, Guanglei Zhu, Eric Heiden, Dylan Turpin, Jingzhou Liu, Ming C. Lin, Miles Macklin, Animesh Garg |
| 2023 | CoRL | Geometry Matching for Multi-Embodiment Grasping. | Maria Attarian, Muhammad Adil Asif, Jingzhou Liu, Ruthrash Hari, Animesh Garg, Igor Gilitschenski, Jonathan Tompson |
| 2023 | CoRL | Composable Part-Based Manipulation. | Weiyu Liu, Jiayuan Mao, Joy Hsu, Tucker Hermans, Animesh Garg, Jiajun Wu |
| 2023 | ICLR | SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models. | Ziyi Wu, Nikita Dvornik, Klaus Greff, Thomas Kipf, Animesh Garg |
| 2023 | ICLR | Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward. | Zihan Zhou, Animesh Garg |
| 2023 | ICRA | nerf2nerf: Pairwise Registration of Neural Radiance Fields. | Lily Goli, Daniel Rebain, Sara Sabour, Animesh Garg, Andrea Tagliasacchi |
| 2023 | ICRA | ProgPrompt: Generating Situated Robot Task Plans using Large Language Models. | Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg |
| 2023 | ICRA | Fast-Grasp'D: Dexterous Multi-finger Grasp Generation Through Differentiable Simulation. | Dylan Turpin, Tao Zhong, Shutong Zhang, Guanglei Zhu, Eric Heiden, Miles Macklin, Stavros Tsogkas, Sven J. Dickinson, Animesh Garg |
| 2023 | ICRA | Self-Supervised Learning of Action Affordances as Interaction Modes. | Liquan Wang, Nikita Dvornik, Rafael Dubeau, Mayank Mittal, Animesh Garg |
| 2023 | ICRA | MVTrans: Multi-View Perception of Transparent Objects. | Yi Ru Wang, Yuchi Zhao, Haoping Xu, Sagi Eppel, Aln Aspuru-Guzik, Florian Shkurti, Animesh Garg |
| 2022 | AAAI | Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings. | Matthew Shunshi Zhang, Murat A. Erdogdu, Animesh Garg |
| 2022 | CoRL | Bayesian Object Models for Robotic Interaction with Differentiable Probabilistic Programming. | Krishna Murthy Jatavallabhula, Miles Macklin, Dieter Fox, Animesh Garg, Fabio Ramos |
| 2022 | CoRL | RoboTube: Learning Household Manipulation from Human Videos with Simulated Twin Environments. | Haoyu Xiong, Haoyuan Fu, Jieyi Zhang, Chen Bao, Qiang Zhang, Yongxi Huang, Wenqiang Xu, Animesh Garg, Cewu Lu |
| 2022 | CVPR | Neural Shape Mating: Self-Supervised Object Assembly with Adversarial Shape Priors. | Yun-Chun Chen, Haoda Li, Dylan Turpin, Alec Jacobson, Animesh Garg |
| 2022 | CVPR | X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval. | Satya Krishna Gorti, Nol Vouitsis, Junwei Ma, Keyvan Golestan, Maksims Volkovs, Animesh Garg, Guangwei Yu |
| 2022 | CVPR | Uniform Priors for Data-Efficient Learning. | Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg |
| 2022 | CVPR | Modular Action Concept Grounding in Semantic Video Prediction. | Wei Yu, Wenxin Chen, Songheng Yin, Steve Easterbrook, Animesh Garg |
| 2022 | ECCV | Grasp'D: Differentiable Contact-Rich Grasp Synthesis for Multi-Fingered Hands. | Dylan Turpin, Liquan Wang, Eric Heiden, Yun-Chun Chen, Miles Macklin, Stavros Tsogkas, Sven J. Dickinson, Animesh Garg |
| 2022 | ICLR | Accelerated Policy Learning with Parallel Differentiable Simulation. | Jie Xu, Viktor Makoviychuk, Yashraj Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin |
| 2022 | ICLR | Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning. | Chenjia Bai, Lingxiao Wang, Zhuoran Yang, Zhi-Hong Deng, Animesh Garg, Peng Liu, Zhaoran Wang |
| 2022 | ICLR | Value Gradient weighted Model-Based Reinforcement Learning. | Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand |
| 2022 | ICML | Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. | Matthias Weissenbacher, Samarth Sinha, Animesh Garg, Yoshinobu Kawahara |
| 2022 | IROS | Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger. | Arthur Allshire, Mayank Mittal, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wthrich, Stefan Bauer, Ankur Handa, Animesh Garg |
| 2022 | IROS | Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation. | Mayank Mittal, David Hoeller, Farbod Farshidian, Marco Hutter, Animesh Garg |
| 2022 | WAFR | GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model. | Zhaoming Xie, Xingye Da, Buck Babich, Animesh Garg, Michiel van de Panne |
| 2021 | AAAI | DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. | Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti |
| 2021 | CoRL | A Persistent Spatial Semantic Representation for High-level Natural Language Instruction Execution. | Valts Blukis, Chris Paxton, Dieter Fox, Animesh Garg, Yoav Artzi |
| 2021 | CoRL | S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics. | Samarth Sinha, Ajay Mandlekar, Animesh Garg |
| 2021 | CoRL | Seeing Glass: Joint Point-Cloud and Depth Completion for Transparent Objects. | Haoping Xu, Yi Ru Wang, Sagi Eppel, Aln Aspuru-Guzik, Florian Shkurti, Animesh Garg |
| 2021 | ICLR | Conservative Safety Critics for Exploration. | Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg |
| 2021 | ICLR | C-Learning: Horizon-Aware Cumulative Accessibility Estimation. | Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell, Tong Li, Animesh Garg |
| 2021 | ICLR | Latent Skill Planning for Exploration and Transfer. | Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti |
| 2021 | ICML | Principled Exploration via Optimistic Bootstrapping and Backward Induction. | Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang |
| 2021 | ICML | Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition. | Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar |
| 2021 | ICML | Value Iteration in Continuous Actions, States and Time. | Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg |
| 2021 | ICML | Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. | Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar |
| 2021 | ICRA | LASER: Learning a Latent Action Space for Efficient Reinforcement Learning. | Arthur Allshire, Roberto Martn-Martn, Charles Lin, Shawn Manuel, Silvio Savarese, Animesh Garg |
| 2021 | ICRA | LEAF: Latent Exploration Along the Frontier. | Homanga Bharadhwaj, Animesh Garg, Florian Shkurti |
| 2021 | ICRA | Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects. | Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu |
| 2021 | IROS | Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos. | Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg |
| 2021 | ICRA | Dynamics Randomization Revisited: A Case Study for Quadrupedal Locomotion. | Zhaoming Xie, Xingye Da, Michiel van de Panne, Buck Babich, Animesh Garg |
| 2020 | CoRL | Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion. | Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Anima Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg |
| 2020 | ICML | Angular Visual Hardness. | Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar |
| 2020 | ICML | Semi-Supervised StyleGAN for Disentanglement Learning. | Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Animashree Anandkumar |
| 2020 | ICRA | Motion Reasoning for Goal-Based Imitation Learning. | De-An Huang, Yu-Wei Chao, Chris Paxton, Xinke Deng, Li Fei-Fei, Juan Carlos Niebles, Animesh Garg, Dieter Fox |
| 2020 | ICRA | Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning. | Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, Nathan D. Ratliff, Animesh Garg, Fabio Ramos, Dieter Fox |
| 2020 | ICRA | Controlling Assistive Robots with Learned Latent Actions. | Dylan P. Losey, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Dorsa Sadigh |
| 2020 | ICRA | IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data. | Ajay Mandlekar, Fabio Ramos, Byron Boots, Silvio Savarese, Li Fei-Fei, Animesh Garg, Dieter Fox |
| 2020 | IROS | Visuomotor Mechanical Search: Learning to Retrieve Target Objects in Clutter. | Andrey Kurenkov, Joseph Taglic, Rohun Kulkarni, Marcus Dominguez-Kuhne, Animesh Garg, Roberto Martn-Martn, Silvio Savarese |
| 2020 | UAI | OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation. | Hongyu Ren, Yuke Zhu, Jure Leskovec, Animashree Anandkumar, Animesh Garg |
| 2019 | CoRL | Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation. | Kuan Fang, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei |
| 2019 | CoRL | AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers. | Andrey Kurenkov, Ajay Mandlekar, Roberto Martin Martin, Silvio Savarese, Animesh Garg |
| 2019 | CVPR | Neural Task Graphs: Generalizing to Unseen Tasks From a Single Video Demonstration. | De-An Huang, Suraj Nair, Danfei Xu, Yuke Zhu, Animesh Garg, Li Fei-Fei, Silvio Savarese, Juan Carlos Niebles |
| 2019 | ICRA | Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter. | Michael Danielczuk, Andrey Kurenkov, Ashwin Balakrishna, Matthew Matl, David Wang, Roberto Martn-Martn, Animesh Garg, Silvio Savarese, Ken Goldberg |
| 2019 | ICRA | Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks. | Michelle A. Lee, Yuke Zhu, Krishnan Srinivasan, Parth Shah, Silvio Savarese, Li Fei-Fei, Animesh Garg, Jeannette Bohg |
| 2019 | IROS | Continuous Relaxation of Symbolic Planner for One-Shot Imitation Learning. | De-An Huang, Danfei Xu, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei, Juan Carlos Niebles |
| 2019 | IROS | Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity. | Ajay Mandlekar, Jonathan Booher, Max Spero, Albert Tung, Anchit Gupta, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei |
| 2019 | IROS | Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks. | Roberto Martn-Martn, Michelle A. Lee, Rachel Gardner, Silvio Savarese, Jeannette Bohg, Animesh Garg |
| 2018 | CoRL | ROBOTURK: A Crowdsourcing Platform for Robotic Skill Learning through Imitation. | Ajay Mandlekar, Yuke Zhu, Animesh Garg, Jonathan Booher, Max Spero, Albert Tung, Julian Gao, John Emmons, Anchit Gupta, Emre Orbay, Silvio Savarese, Li Fei-Fei |
| 2018 | CVPR | Finding "It": Weakly-Supervised Reference-Aware Visual Grounding in Instructional Videos. | De-An Huang, Shyamal Buch, Lucio M. Dery, Animesh Garg, Li Fei-Fei, Juan Carlos Niebles |
| 2018 | ICRA | Neural Task Programming: Learning to Generalize Across Hierarchical Tasks. | Danfei Xu, Suraj Nair, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, Silvio Savarese |
| 2018 | WACV | DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image. | Andrey Kurenkov, Jingwei Ji, Animesh Garg, Viraj Mehta, JunYoung Gwak, Christopher B. Choy, Silvio Savarese |
| 2017 | IROS | Adversarially Robust Policy Learning: Active construction of physically-plausible perturbations. | Ajay Mandlekar, Yuke Zhu, Animesh Garg, Li Fei-Fei, Silvio Savarese |
| 2017 | ICRA | Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning. | Brijen Thananjeyan, Animesh Garg, Sanjay Krishnan, Carolyn Chen, Lauren Miller, Ken Goldberg |
| 2017 | ISRR | AdaPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems. | James Harrison, Animesh Garg, Boris Ivanovic, Yuke Zhu, Silvio Savarese, Li Fei-Fei, Marco Pavone |
| 2016 | ICRA | TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning. | Adithyavairavan Murali, Animesh Garg, Sanjay Krishnan, Florian T. Pokorny, Pieter Abbeel, Trevor Darrell, Ken Goldberg |
| 2016 | ICRA | Automating multi-throw multilateral surgical suturing with a mechanical needle guide and sequential convex optimization. | Siddarth Sen, Animesh Garg, David V. Gealy, Stephen McKinley, Yiming Jen, Ken Goldberg |
| 2016 | WAFR | SWIRL: A SequentialWindowed Inverse Reinforcement Learning Algorithm for Robot Tasks With Delayed Rewards. | Sanjay Krishnan, Animesh Garg, Richard Liaw, Brijen Thananjeyan, Lauren Miller, Florian T. Pokorny, Ken Goldberg |
| 2015 | ICRA | Learning by observation for surgical subtasks: Multilateral cutting of 3D viscoelastic and 2D Orthotropic Tissue Phantoms. | Adithyavairavan Murali, Siddarth Sen, Ben Kehoe, Animesh Garg, Seth McFarland, Sachin Patil, W. Douglas Boyd, Susan Lim, Pieter Abbeel, Kenneth Y. Goldberg |
| 2015 | ISRR | Transition State Clustering: Unsupervised Surgical Trajectory Segmentation for Robot Learning. | Sanjay Krishnan, Animesh Garg, Sachin Patil, Colin Lea, Gregory D. Hager, Pieter Abbeel, Ken Goldberg |