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2020 – today
- 2023
[j12]Eric Heiden, Miles Macklin, Yashraj S. Narang, Dieter Fox, Animesh Garg, Fabio Ramos:
DiSECt: a differentiable simulator for parameter inference and control in robotic cutting. Auton. Robots 47(5): 549-578 (2023)- [j11]Michael Lutter
, Boris Belousov, Shie Mannor, Dieter Fox, Animesh Garg, Jan Peters:
Continuous-Time Fitted Value Iteration for Robust Policies. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5534-5548 (2023) - [j10]Mayank Mittal, Calvin Yu, Qinxi Yu, Jingzhou Liu, Nikita Rudin, David Hoeller, Jia Lin Yuan, Ritvik Singh, Yunrong Guo, Hammad Mazhar, Ajay Mandlekar, Buck Babich, Gavriel State, Marco Hutter, Animesh Garg:
Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments. IEEE Robotics Autom. Lett. 8(6): 3740-3747 (2023) - [c90]Ziyi Wu, Nikita Dvornik, Klaus Greff, Thomas Kipf, Animesh Garg:
SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models. ICLR 2023 - [c89]Zihan Zhou, Animesh Garg:
Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward. ICLR 2023 - [c88]Yi Ru Wang, Yuchi Zhao, Haoping Xu, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
MVTrans: Multi-View Perception of Transparent Objects. ICRA 2023: 3771-3778 - [c87]Liquan Wang, Nikita Dvornik, Rafael Dubeau, Mayank Mittal, Animesh Garg:
Self-Supervised Learning of Action Affordances as Interaction Modes. ICRA 2023: 7279-7286 - [c86]Dylan Turpin, Tao Zhong, Shutong Zhang, Guanglei Zhu, Eric Heiden, Miles Macklin, Stavros Tsogkas, Sven J. Dickinson, Animesh Garg:
Fast-Grasp'D: Dexterous Multi-finger Grasp Generation Through Differentiable Simulation. ICRA 2023: 8082-8089 - [c85]Lily Goli, Daniel Rebain, Sara Sabour, Animesh Garg, Andrea Tagliasacchi:
nerf2nerf: Pairwise Registration of Neural Radiance Fields. ICRA 2023: 9354-9361 - [c84]Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg:
ProgPrompt: Generating Situated Robot Task Plans using Large Language Models. ICRA 2023: 11523-11530 - [i101]Mayank Mittal, Calvin Yu, Qinxi Yu, Jingzhou Liu, Nikita Rudin, David Hoeller, Jia Lin Yuan, Pooria Poorsarvi Tehrani, Ritvik Singh, Yunrong Guo, Hammad Mazhar, Ajay Mandlekar, Buck Babich, Gavriel State, Marco Hutter, Animesh Garg:
ORBIT: A Unified Simulation Framework for Interactive Robot Learning Environments. CoRR abs/2301.04195 (2023) - [i100]Yi Ru Wang, Yuchi Zhao, Haoping Xu, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
MVTrans: Multi-View Perception of Transparent Objects. CoRR abs/2302.11683 (2023) - [i99]Marta Skreta, Naruki Yoshikawa, Sebastian Arellano-Rubach, Zhi Ji, Lasse Bjørn Kristensen, Kourosh Darvish, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting. CoRR abs/2303.14100 (2023) - [i98]Chaitanya Devaguptapu, Samarth Sinha, K. J. Joseph, Vineeth N. Balasubramanian, Animesh Garg:
Δ-Networks for Efficient Model Patching. CoRR abs/2303.14772 (2023) - [i97]Nikita Dvornik, Isma Hadji, Ran Zhang, Konstantinos G. Derpanis, Animesh Garg, Richard P. Wildes, Allan D. Jepson:
StepFormer: Self-supervised Step Discovery and Localization in Instructional Videos. CoRR abs/2304.13265 (2023) - [i96]Zihan Zhou, Animesh Garg:
Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward. CoRR abs/2305.00508 (2023) - [i95]Ziyi Wu, Jingyu Hu, Wuyue Lu, Igor Gilitschenski, Animesh Garg:
SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models. CoRR abs/2305.11281 (2023) - [i94]Liquan Wang, Nikita Dvornik, Rafael Dubeau, Mayank Mittal, Animesh Garg:
Self-Supervised Learning of Action Affordances as Interaction Modes. CoRR abs/2305.17565 (2023) - [i93]Dylan Turpin, Tao Zhong, Shutong Zhang, Guanglei Zhu, Jingzhou Liu, Ritvik Singh, Eric Heiden, Miles Macklin, Stavros Tsogkas, Sven J. Dickinson, Animesh Garg:
Fast-Grasp'D: Dexterous Multi-finger Grasp Generation Through Differentiable Simulation. CoRR abs/2306.08132 (2023) - 2022
- [j9]Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh:
Learning latent actions to control assistive robots. Auton. Robots 46(1): 115-147 (2022) - [j8]Aysegul Dundar, Kevin J. Shih, Animesh Garg, Robert Pottorf, Andrew Tao, Bryan Catanzaro:
Unsupervised Disentanglement of Pose, Appearance and Background from Images and Videos. IEEE Trans. Pattern Anal. Mach. Intell. 44(7): 3883-3894 (2022) - [j7]Jiankai Sun, De-An Huang, Bo Lu, Yun-Hui Liu, Bolei Zhou, Animesh Garg:
PlaTe: Visually-Grounded Planning With Transformers in Procedural Tasks. IEEE Robotics Autom. Lett. 7(2): 4924-4930 (2022) - [c83]Matthew Shunshi Zhang, Murat A. Erdogdu, Animesh Garg:
Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings. AAAI 2022: 9066-9073 - [c82]Qizhen Zhang, Christopher Lu, Animesh Garg, Jakob N. Foerster:
Centralized Model and Exploration Policy for Multi-Agent RL. AAMAS 2022: 1500-1508 - [c81]Haoyu Xiong, Haoyuan Fu, Jieyi Zhang, Chen Bao, Qiang Zhang, Yongxi Huang, Wenqiang Xu, Animesh Garg, Cewu Lu:
RoboTube: Learning Household Manipulation from Human Videos with Simulated Twin Environments. CoRL 2022: 1-10 - [c80]Krishna Murthy Jatavallabhula, Miles Macklin, Dieter Fox, Animesh Garg, Fabio Ramos:
Bayesian Object Models for Robotic Interaction with Differentiable Probabilistic Programming. CoRL 2022: 1563-1574 - [c79]Wei Yu, Wenxin Chen, Songheng Yin, Steve Easterbrook, Animesh Garg:
Modular Action Concept Grounding in Semantic Video Prediction. CVPR 2022: 3595-3604 - [c78]Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg:
Uniform Priors for Data-Efficient Learning. CVPR Workshops 2022: 4016-4027 - [c77]Satya Krishna Gorti, Noël Vouitsis, Junwei Ma, Keyvan Golestan, Maksims Volkovs, Animesh Garg, Guangwei Yu:
X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval. CVPR 2022: 4996-5005 - [c76]Yun-Chun Chen, Haoda Li, Dylan Turpin, Alec Jacobson, Animesh Garg:
Neural Shape Mating: Self-Supervised Object Assembly with Adversarial Shape Priors. CVPR 2022: 12714-12723 - [c75]Dylan Turpin, Liquan Wang, Eric Heiden, Yun-Chun Chen, Miles Macklin, Stavros Tsogkas, Sven J. Dickinson, Animesh Garg:
Grasp'D: Differentiable Contact-Rich Grasp Synthesis for Multi-Fingered Hands. ECCV (6) 2022: 201-221 - [c74]Jie Xu, Viktor Makoviychuk, Yashraj S. Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin:
Accelerated Policy Learning with Parallel Differentiable Simulation. ICLR 2022 - [c73]Chenjia Bai, Lingxiao Wang, Zhuoran Yang, Zhi-Hong Deng, Animesh Garg, Peng Liu, Zhaoran Wang:
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning. ICLR 2022 - [c72]Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand:
Value Gradient weighted Model-Based Reinforcement Learning. ICLR 2022 - [c71]Matthias Weissenbacher, Samarth Sinha, Animesh Garg, Yoshinobu Kawahara:
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. ICML 2022: 23645-23667 - [c70]Mayank Mittal, David Hoeller, Farbod Farshidian, Marco Hutter, Animesh Garg:
Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation. IROS 2022: 1647-1654 - [c69]Arthur Allshire, Mayank Mittal, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Ankur Handa, Animesh Garg:
Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger. IROS 2022: 11802-11809 - [c68]Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon:
Experience Replay with Likelihood-free Importance Weights. L4DC 2022: 110-123 - [c67]Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg:
MoCoDA: Model-based Counterfactual Data Augmentation. NeurIPS 2022 - [c66]Silvia Sellán, Yun-Chun Chen, Ziyi Wu, Animesh Garg, Alec Jacobson:
Breaking Bad: A Dataset for Geometric Fracture and Reassembly. NeurIPS 2022 - [c65]Mohan Zhang, Xiaozhou Wang, Benjamin Decardi-Nelson, Bo Song, An Zhang, Jinfeng Liu, Sile Tao, Jiayi Cheng, Xiaohong Liu, Dengdeng Yu, Matthew Poon, Animesh Garg:
SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments. NeurIPS 2022 - [c64]Zhaoming Xie, Xingye Da, Buck Babich, Animesh Garg, Michiel van de Panne:
GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model. WAFR 2022: 523-539 - [i92]Chenjia Bai, Lingxiao Wang, Zhuoran Yang, Zhihong Deng, Animesh Garg, Peng Liu, Zhaoran Wang:
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning. CoRR abs/2202.11566 (2022) - [i91]Eric Heiden, Miles Macklin, Yashraj S. Narang, Dieter Fox, Animesh Garg, Fabio Ramos:
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting. CoRR abs/2203.10263 (2022) - [i90]Satya Krishna Gorti, Noël Vouitsis, Junwei Ma, Keyvan Golestan, Maksims Volkovs, Animesh Garg, Guang Wei Yu:
X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval. CoRR abs/2203.15086 (2022) - [i89]Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand:
Value Gradient weighted Model-Based Reinforcement Learning. CoRR abs/2204.01464 (2022) - [i88]Jie Xu, Viktor Makoviychuk, Yashraj S. Narang, Fabio T. Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin:
Accelerated Policy Learning with Parallel Differentiable Simulation. CoRR abs/2204.07137 (2022) - [i87]Yun-Chun Chen, Haoda Li, Dylan Turpin, Alec Jacobson, Animesh Garg:
Neural Shape Mating: Self-Supervised Object Assembly with Adversarial Shape Priors. CoRR abs/2205.14886 (2022) - [i86]Mohan Zhang, Xiaozhou Wang, Benjamin Decardi-Nelson, Bo Song, An Zhang, Jinfeng Liu, Sile Tao, Jiayi Cheng, Xiaohong Liu, Dengdeng Yu, Matthew Poon, Animesh Garg:
SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments. CoRR abs/2206.08851 (2022) - [i85]Yun-Chun Chen, Adithyavairavan Murali, Balakumar Sundaralingam, Wei Yang, Animesh Garg, Dieter Fox:
Neural Motion Fields: Encoding Grasp Trajectories as Implicit Value Functions. CoRR abs/2206.14854 (2022) - [i84]Dylan Turpin, Liquan Wang, Eric Heiden, Yun-Chun Chen, Miles Macklin, Stavros Tsogkas, Sven J. Dickinson, Animesh Garg:
Grasp'D: Differentiable Contact-rich Grasp Synthesis for Multi-fingered Hands. CoRR abs/2208.12250 (2022) - [i83]Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg:
ProgPrompt: Generating Situated Robot Task Plans using Large Language Models. CoRR abs/2209.11302 (2022) - [i82]Maria Attarian, Advaya Gupta, Ziyi Zhou, Wei Yu, Igor Gilitschenski, Animesh Garg:
See, Plan, Predict: Language-guided Cognitive Planning with Video Prediction. CoRR abs/2210.03825 (2022) - [i81]Ziyi Wu, Nikita Dvornik, Klaus Greff, Thomas Kipf, Animesh Garg:
SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models. CoRR abs/2210.05861 (2022) - [i80]Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg:
MoCoDA: Model-based Counterfactual Data Augmentation. CoRR abs/2210.11287 (2022) - [i79]Silvia Sellán, Yun-Chun Chen, Ziyi Wu, Animesh Garg, Alec Jacobson:
Breaking Bad: A Dataset for Geometric Fracture and Reassembly. CoRR abs/2210.11463 (2022) - [i78]Lily Goli, Daniel Rebain, Sara Sabour, Animesh Garg, Andrea Tagliasacchi:
nerf2nerf: Pairwise Registration of Neural Radiance Fields. CoRR abs/2211.01600 (2022) - [i77]Amir Rasouli, Randy Goebel, Matthew E. Taylor, Iuliia Kotseruba, Soheil Alizadeh, Tianpei Yang, Montgomery Alban, Florian Shkurti, Yuzheng Zhuang, Adam Scibior, Kasra Rezaee, Animesh Garg, David Meger, Jun Luo, Liam Paull, Weinan Zhang, Xinyu Wang, Xi Chen:
NeurIPS 2022 Competition: Driving SMARTS. CoRR abs/2211.07545 (2022) - [i76]Naruki Yoshikawa, Andrew Zou Li, Kourosh Darvish, Yuchi Zhao, Haoping Xu, Alán Aspuru-Guzik, Animesh Garg, Florian Shkurti:
An Adaptive Robotics Framework for Chemistry Lab Automation. CoRR abs/2212.09672 (2022) - [i75]Riashat Islam, Samarth Sinha, Homanga Bharadhwaj, Samin Yeasar Arnob, Zhuoran Yang, Animesh Garg, Zhaoran Wang, Lihong Li, Doina Precup:
Offline Policy Optimization in RL with Variance Regularizaton. CoRR abs/2212.14405 (2022) - 2021
- [c63]Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti:
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. AAAI 2021: 9666-9674 - [c62]Valts Blukis, Chris Paxton, Dieter Fox, Animesh Garg, Yoav Artzi:
A Persistent Spatial Semantic Representation for High-level Natural Language Instruction Execution. CoRL 2021: 706-717 - [c61]Haoping Xu, Yi Ru Wang, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
Seeing Glass: Joint Point-Cloud and Depth Completion for Transparent Objects. CoRL 2021: 827-838 - [c60]Samarth Sinha, Ajay Mandlekar, Animesh Garg:
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics. CoRL 2021: 907-917 - [c59]Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg:
Conservative Safety Critics for Exploration. ICLR 2021 - [c58]Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell, Tong Li, Animesh Garg:
C-Learning: Horizon-Aware Cumulative Accessibility Estimation. ICLR 2021 - [c57]Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti:
Latent Skill Planning for Exploration and Transfer. ICLR 2021 - [c56]Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang:
Principled Exploration via Optimistic Bootstrapping and Backward Induction. ICML 2021: 577-587 - [c55]Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar:
Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition. ICML 2021: 6860-6870 - [c54]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Value Iteration in Continuous Actions, States and Time. ICML 2021: 7224-7234 - [c53]Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar:
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. ICML 2021: 7301-7312 - [c52]Homanga Bharadhwaj, Animesh Garg, Florian Shkurti:
LEAF: Latent Exploration Along the Frontier. ICRA 2021: 677-684 - [c51]Zhaoming Xie, Xingye Da, Michiel van de Panne, Buck Babich, Animesh Garg:
Dynamics Randomization Revisited: A Case Study for Quadrupedal Locomotion. ICRA 2021: 4955-4961 - [c50]Arthur Allshire, Roberto Martín-Martín, Charles Lin, Shawn Manuel, Silvio Savarese, Animesh Garg:
LASER: Learning a Latent Action Space for Efficient Reinforcement Learning. ICRA 2021: 6650-6656 - [c49]Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu:
Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects. ICRA 2021: 7540-7547 - [c48]Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg:
Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos. IROS 2021: 7827-7834 - [c47]Stefan Bauer, Manuel Wüthrich, Felix Widmaier, Annika Buchholz, Sebastian Stark, Anirudh Goyal, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vincent Berenz, Vaibhav Agrawal, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Takahiro Maeda, Harshit Sikchi, Jilong Wang, Qingfeng Yao, Shuyu Yang, Robert McCarthy, Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens, Kevin McGuinness, Noel E. O'Connor, Stephen J. Redmond, Bernhard Schölkopf:
Real Robot Challenge: A Robotics Competition in the Cloud. NeurIPS (Competition and Demos) 2021: 190-204 - [c46]Michael Poli, Stefano Massaroli, Luca Scimeca, Sanghyuk Chun, Seong Joon Oh, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg:
Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions. NeurIPS 2021: 9977-9989 - [c45]Nikita Dvornik, Isma Hadji, Konstantinos G. Derpanis, Animesh Garg, Allan D. Jepson:
Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers. NeurIPS 2021: 13782-13793 - [c44]Chenjia Bai, Lingxiao Wang, Lei Han, Animesh Garg, Jianye Hao, Peng Liu, Zhaoran Wang:
Dynamic Bottleneck for Robust Self-Supervised Exploration. NeurIPS 2021: 17007-17020 - [c43]Eric Heiden, Miles Macklin, Yashraj S. Narang, Dieter Fox, Animesh Garg, Fabio Ramos:
DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting. Robotics: Science and Systems 2021 - [c42]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Robust Value Iteration for Continuous Control Tasks. Robotics: Science and Systems 2021 - [c41]Dylan Turpin, Liquan Wang, Stavros Tsogkas, Sven J. Dickinson, Animesh Garg:
GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels. Robotics: Science and Systems 2021 - [i74]Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg:
Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos. CoRR abs/2101.07241 (2021) - [i73]Samarth Sinha, Animesh Garg:
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning. CoRR abs/2103.06326 (2021) - [i72]Mayank Mittal, David Hoeller, Farbod Farshidian, Marco Hutter, Animesh Garg:
Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation. CoRR abs/2103.10534 (2021) - [i71]Arthur Allshire, Roberto Martín-Martín, Charles Lin, Shawn Manuel, Silvio Savarese, Animesh Garg:
LASER: Learning a Latent Action Space for Efficient Reinforcement Learning. CoRR abs/2103.15793 (2021) - [i70]Zhaoming Xie, Xingye Da, Buck Babich, Animesh Garg, Michiel van de Panne:
GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model. CoRR abs/2104.09771 (2021) - [i69]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Value Iteration in Continuous Actions, States and Time. CoRR abs/2105.04682 (2021) - [i68]Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang:
Principled Exploration via Optimistic Bootstrapping and Backward Induction. CoRR abs/2105.06022 (2021) - [i67]Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Animashree Anandkumar:
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition. CoRR abs/2105.08692 (2021) - [i66]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Robust Value Iteration for Continuous Control Tasks. CoRR abs/2105.12189 (2021) - [i65]Eric Heiden, Miles Macklin, Yashraj S. Narang, Dieter Fox, Animesh Garg, Fabio Ramos:
DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting. CoRR abs/2105.12244 (2021) - [i64]Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar:
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. CoRR abs/2106.00136 (2021) - [i63]Michael Poli, Stefano Massaroli, Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg:
Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions. CoRR abs/2106.04165 (2021) - [i62]Dylan Turpin, Liquan Wang, Stavros Tsogkas, Sven J. Dickinson, Animesh Garg:
GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels. CoRR abs/2106.14973 (2021) - [i61]Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh:
Learning Latent Actions to Control Assistive Robots. CoRR abs/2107.02907 (2021) - [i60]Valts Blukis, Chris Paxton, Dieter Fox, Animesh Garg, Yoav Artzi:
A Persistent Spatial Semantic Representation for High-level Natural Language Instruction Execution. CoRR abs/2107.05612 (2021) - [i59]Qizhen Zhang, Christopher Lu, Animesh Garg, Jakob N. Foerster:
Centralized Model and Exploration Policy for Multi-Agent RL. CoRR abs/2107.06434 (2021) - [i58]Arthur Allshire, Mayank Mittal, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Ankur Handa, Animesh Garg:
Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger. CoRR abs/2108.09779 (2021) - [i57]Nikita Dvornik, Isma Hadji, Konstantinos G. Derpanis, Animesh Garg, Allan D. Jepson:
Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers. CoRR abs/2108.11996 (2021) - [i56]Jiankai Sun, De-An Huang, Bo Lu, Yun-Hui Liu, Bolei Zhou, Animesh Garg:
PlaTe: Visually-Grounded Planning with Transformers in Procedural Tasks. CoRR abs/2109.04869 (2021) - [i55]Stefan Bauer, Felix Widmaier, Manuel Wüthrich, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Charles B. Schaff, Takahiro Maeda, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Annika Buchholz, Sebastian Stark, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bernhard Schölkopf:
A Robot Cluster for Reproducible Research in Dexterous Manipulation. CoRR abs/2109.10957 (2021) - [i54]Homanga Bharadhwaj, De-An Huang, Chaowei Xiao, Anima Anandkumar, Animesh Garg:
Auditing AI models for Verified Deployment under Semantic Specifications. CoRR abs/2109.12456 (2021) - [i53]Haoping Xu, Yi Ru Wang, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects. CoRR abs/2110.00087 (2021) - [i52]Michael Lutter, Boris Belousov, Shie Mannor, Dieter Fox, Animesh Garg, Jan Peters:
Continuous-Time Fitted Value Iteration for Robust Policies. CoRR abs/2110.01954 (2021) - [i51]Chenjia Bai, Lingxiao Wang, Lei Han, Animesh Garg, Jianye Hao, Peng Liu, Zhaoran Wang:
Dynamic Bottleneck for Robust Self-Supervised Exploration. CoRR abs/2110.10735 (2021) - [i50]Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar:
Reinforcement Learning in Factored Action Spaces using Tensor Decompositions. CoRR abs/2110.14538 (2021) - [i49]Matthew Shunshi Zhang, Murat A. Erdogdu, Animesh Garg:
Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings. CoRR abs/2111.00185 (2021) - [i48]Matthias Weissenbacher, Samarth Sinha, Animesh Garg, Yoshinobu Kawahara:
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. CoRR abs/2111.01365 (2021) - 2020
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