Initial experiments toward automated robotic implantation of skew-line needle arrangements for HDR brachytherapy. - Animesh Garg; Timmy Siauw; Dmitry Berenson; J. Adam M. Cunha; I-Chow Hsu; Jean Pouliot; Dan Stoianovici; Ken Goldberg (CASE, 2012)

An algorithm for computing customized 3D printed implants with curvature constrained channels for enhancing intracavitary brachytherapy radiation delivery. - Animesh Garg; Sachin Patil; Timmy Siauw; J. Adam M. Cunha; I-Chow Hsu; Pieter Abbeel; Jean Pouliot; Ken Goldberg (CASE, 2013)

Robot-Guided Open-Loop Insertion of Skew-Line Needle Arrangements for High Dose Rate Brachytherapy. - Animesh Garg; Timmy Siauw; Dmitry Berenson; J. Adam M. Cunha; I-Chow Hsu; Jean Pouliot; Dan Stoianovici; Ken Goldberg (IEEE Trans Autom. Sci. Eng., 2013)

Exact reachability analysis for planning skew-line needle arrangements for automated brachytherapy. - Animesh Garg; Timmy Siauw; Guang Yang; Sachin Patil; J. Adam M. Cunha; I-Chow Hsu; Jean Pouliot; Alper Atamtürk; Kenneth Y. Goldberg (CASE, 2014)

A single-use haptic palpation probe for locating subcutaneous blood vessels in robot-assisted minimally invasive surgery. - Stephen McKinley; Animesh Garg; Siddarth Sen; Rishi Kapadia; Adithyavairavan Murali; Kirk A. Nichols; Susan Lim; Sachin Patil; Pieter Abbeel; Allison M. Okamura; Ken Goldberg (CASE, 2015)

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 (ICRA, 2015)

Tumor localization using automated palpation with Gaussian Process Adaptive Sampling. - Animesh Garg; Siddarth Sen; Rishi Kapadia; Yiming Jen; Stephen McKinley; Lauren Miller; Ken Goldberg (CASE, 2016)

An interchangeable surgical instrument system with application to supervised automation of multilateral tumor resection. - Stephen McKinley; Animesh Garg; Siddarth Sen; David V. Gealy; Jonathan P. McKinley; Yiming Jen; Menglong Guo; Walter Doug Boyd; Ken Goldberg (CASE, 2016)

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 (ICRA, 2016)

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 (ICRA, 2016)

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 (WAFR, 2016)

HIRL: Hierarchical Inverse Reinforcement Learning for Long-Horizon Tasks with Delayed Rewards. - Sanjay Krishnan; Animesh Garg; Richard Liaw; Lauren Miller; Florian T. Pokorny; Ken Goldberg (CoRR, 2016)

Optimization and Design for Automation of Brachytherapy Delivery and Learning Robot-Assisted Surgical Sub-Tasks. - Animesh Garg (2016)

Weakly Supervised 3D Reconstruction with Adversarial Constraint. - JunYoung Gwak; Christopher B. Choy; Manmohan Chandraker; Animesh Garg; Silvio Savarese (3DV, 2017)

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 (ICRA, 2017)

Adversarially Robust Policy Learning: Active construction of physically-plausible perturbations. - Ajay Mandlekar; Yuke Zhu; Animesh Garg; Li Fei-Fei 001; Silvio Savarese (IROS, 2017)

AdaPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems. - James Harrison; Animesh Garg; Boris Ivanovic; Yuke Zhu; Silvio Savarese; Li Fei-Fei 001; Marco Pavone 001 (ISRR, 2017)

Weakly Supervised Generative Adversarial Networks for 3D Reconstruction. - JunYoung Gwak; Christopher B. Choy; Animesh Garg; Manmohan Chandraker; Silvio Savarese (CoRR, 2017)

Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning. - Richard Liaw; Sanjay Krishnan; Animesh Garg; Daniel Crankshaw; Joseph E. Gonzalez; Ken Goldberg (CoRR, 2017)

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 (Int. J. Robotics Res., 2017)

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 001 (CoRL, 2018)

Finding "It": Weakly-Supervised Reference-Aware Visual Grounding in Instructional Videos. - De-An Huang; Shyamal Buch; Lucio M. Dery; Animesh Garg; Li Fei-Fei 001; Juan Carlos Niebles (CVPR, 2018)

Neural Task Programming: Learning to Generalize Across Hierarchical Tasks. - Danfei Xu; Suraj Nair 003; Yuke Zhu; Julian Gao; Animesh Garg; Li Fei-Fei 001; Silvio Savarese (ICRA, 2018)

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 (WACV, 2018)

Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation. - Kuan Fang; Yuke Zhu; Animesh Garg; Silvio Savarese; Li Fei-Fei 001 (CoRL, 2019)

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 (CoRL, 2019)

Neural Task Graphs: Generalizing to Unseen Tasks From a Single Video Demonstration. - De-An Huang; Suraj Nair 003; Danfei Xu; Yuke Zhu; Animesh Garg; Li Fei-Fei 001; Silvio Savarese; Juan Carlos Niebles (CVPR, 2019)

Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter. - Michael Danielczuk; Andrey Kurenkov; Ashwin Balakrishna; Matthew Matl; David Wang; Roberto Martín-Martín; Animesh Garg; Silvio Savarese; Ken Goldberg (ICRA, 2019)

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 003; Silvio Savarese; Li Fei-Fei 001; Animesh Garg; Jeannette Bohg (ICRA, 2019)

Continuous Relaxation of Symbolic Planner for One-Shot Imitation Learning. - De-An Huang; Danfei Xu; Yuke Zhu; Animesh Garg; Silvio Savarese; Li Fei-Fei 001; Juan Carlos Niebles (IROS, 2019)

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 001 (IROS, 2019)

Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks. - Roberto Martín-Martín; Michelle A. Lee; Rachel Gardner; Silvio Savarese; Jeannette Bohg; Animesh Garg (IROS, 2019)

Video Interpolation and Prediction with Unsupervised Landmarks. - Kevin J. Shih; Aysegul Dundar; Animesh Garg; Robert Pottorf; Andrew Tao; Bryan Catanzaro (CoRR, 2019)

A Programmable Approach to Model Compression. - Vinu Joseph; Saurav Muralidharan; Animesh Garg; Michael Garland; Ganesh Gopalakrishnan (CoRR, 2019)

IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data. - Ajay Mandlekar; Fabio Ramos 001; Byron Boots; Li Fei-Fei 001; Animesh Garg; Dieter Fox (CoRR, 2019)

InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers. - Tan M. Nguyen; Animesh Garg; Richard G. Baraniuk; Anima Anandkumar (CoRR, 2019)

SWIRL: A sequential windowed 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 (Int. J. Robotics Res., 2019)

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 (CoRL, 2020)

Angular Visual Hardness. - Beidi Chen; Weiyang Liu; Zhiding Yu; Jan Kautz; Anshumali Shrivastava; Animesh Garg; Animashree Anandkumar (ICML, 2020)

Semi-Supervised StyleGAN for Disentanglement Learning. - Weili Nie; Tero Karras; Animesh Garg; Shoubhik Debnath; Anjul Patney; Ankit B. Patel; Animashree Anandkumar (ICML, 2020)

Motion Reasoning for Goal-Based Imitation Learning. - De-An Huang; Yu-Wei Chao; Chris Paxton; Xinke Deng; Li Fei-Fei 001; Juan Carlos Niebles; Animesh Garg; Dieter Fox (ICRA, 2020)

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 001; Dieter Fox (ICRA, 2020)

Controlling Assistive Robots with Learned Latent Actions. - Dylan P. Losey; Krishnan Srinivasan; Ajay Mandlekar; Animesh Garg; Dorsa Sadigh (ICRA, 2020)

IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data. - Ajay Mandlekar; Fabio Ramos 001; Byron Boots; Silvio Savarese; Li Fei-Fei 001; Animesh Garg; Dieter Fox (ICRA, 2020)

Visuomotor Mechanical Search: Learning to Retrieve Target Objects in Clutter. - Andrey Kurenkov; Joseph Taglic; Rohun Kulkarni; Marcus Dominguez-Kuhne; Animesh Garg; Roberto Martín-Martín; Silvio Savarese (IROS, 2020)

Causal Discovery in Physical Systems from Videos. - Yunzhu Li; Antonio Torralba 001; Anima Anandkumar; Dieter Fox; Animesh Garg (NeurIPS, 2020)

Counterfactual Data Augmentation using Locally Factored Dynamics. - Silviu Pitis; Elliot Creager; Animesh Garg (NeurIPS, 2020)

Curriculum By Smoothing. - Samarth Sinha; Animesh Garg; Hugo Larochelle (NeurIPS, 2020)

OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation. - Hongyu Ren; Yuke Zhu; Jure Leskovec; Animashree Anandkumar; Animesh Garg (UAI, 2020)

Curriculum By Texture. - Samarth Sinha; Animesh Garg; Hugo Larochelle (CoRR, 2020)

Dynamics-Aware Latent Space Reachability for Exploration in Temporally-Extended Tasks. - Homanga Bharadhwaj; Animesh Garg; Florian Shkurti (CoRR, 2020)

Maximum Entropy Models for Fast Adaptation. - Samarth Sinha; Anirudh Goyal; Animesh Garg (CoRR, 2020)

De-anonymization of authors through arXiv submissions during double-blind review. - Homanga Bharadhwaj; Dylan Turpin; Animesh Garg; Ashton Anderson (CoRR, 2020)

Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors. - Tim D. Barfoot; Jessica Burgner-Kahrs; Eric D. Diller; Animesh Garg; Andrew A. Goldenberg; Jonathan Kelly; Xinyu Liu 002; Hani E. Naguib; Goldie Nejat; Angela P. Schoellig; Florian Shkurti; Hallie Siegel; et al. (CoRR, 2020)

D2RL: Deep Dense Architectures in Reinforcement Learning. - Samarth Sinha; Homanga Bharadhwaj; Aravind Srinivas; Animesh Garg (CoRR, 2020)

Solving Physics Puzzles by Reasoning about Paths. - Augustin Harter; Andrew Melnik; Gaurav Kumar; Dhruv Agarwal 002; Animesh Garg; Helge J. Ritter (CoRR, 2020)

Action Concept Grounding Network for Semantically-Consistent Video Generation. - Wei Yu; Wenxin Chen; Steve Easterbrook; Animesh Garg (CoRR, 2020)

Skill Transfer via Partially Amortized Hierarchical Planning. - Kevin Xie; Homanga Bharadhwaj; Danijar Hafner; Animesh Garg; Florian Shkurti (CoRR, 2020)

Learning task-oriented grasping for tool manipulation from simulated self-supervision. - Kuan Fang; Yuke Zhu; Animesh Garg; Andrey Kurenkov; Viraj Mehta; Li Fei-Fei 001; Silvio Savarese (Int. J. Robotics Res., 2020)

A Programmable Approach to Neural Network Compression. - Vinu Joseph; Ganesh Gopalakrishnan; Saurav Muralidharan; Michael Garland; Animesh Garg (IEEE Micro, 2020)

Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks. - Michelle A. Lee; Yuke Zhu; Peter Zachares; Matthew Tan; Krishnan Srinivasan; Silvio Savarese; Li Fei-Fei 001; Animesh Garg; Jeannette Bohg (IEEE Trans. Robotics, 2020)

DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. - Samarth Sinha; Homanga Bharadhwaj; Anirudh Goyal; Hugo Larochelle; Animesh Garg; Florian Shkurti (AAAI, 2021)

A Persistent Spatial Semantic Representation for High-level Natural Language Instruction Execution. - Valts Blukis; Chris Paxton; Dieter Fox; Animesh Garg; Yoav Artzi (CoRL, 2021)

S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics. - Samarth Sinha; Ajay Mandlekar; Animesh Garg (CoRL, 2021)

Seeing Glass: Joint Point-Cloud and Depth Completion for Transparent Objects. - Haoping Xu; Yi Ru Wang; Sagi Eppel; Alán Aspuru-Guzik; Florian Shkurti; Animesh Garg (CoRL, 2021)

Conservative Safety Critics for Exploration. - Homanga Bharadhwaj; Aviral Kumar; Nicholas Rhinehart; Sergey Levine; Florian Shkurti; Animesh Garg (ICLR, 2021)

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 (ICLR, 2021)

Latent Skill Planning for Exploration and Transfer. - Kevin Xie; Homanga Bharadhwaj; Danijar Hafner; Animesh Garg; Florian Shkurti (ICLR, 2021)

Principled Exploration via Optimistic Bootstrapping and Backward Induction. - Chenjia Bai; Lingxiao Wang 003; Lei Han 001; Jianye Hao; Animesh Garg; Peng Liu 008; Zhaoran Wang 001 (ICML, 2021)

Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition. - Bo Liu 042; Qiang Liu 001; Peter Stone; Animesh Garg; Yuke Zhu; Anima Anandkumar (ICML, 2021)

Value Iteration in Continuous Actions, States and Time. - Michael Lutter; Shie Mannor; Jan Peters 001; Dieter Fox; Animesh Garg (ICML, 2021)

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 (ICML, 2021)

LASER: Learning a Latent Action Space for Efficient Reinforcement Learning. - Arthur Allshire; Roberto Martín-Martín; Charles Lin; Shawn Manuel; Silvio Savarese; Animesh Garg (ICRA, 2021)

LEAF: Latent Exploration Along the Frontier. - Homanga Bharadhwaj; Animesh Garg; Florian Shkurti (ICRA, 2021)

Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects. - Xinlei Pan; Animesh Garg; Animashree Anandkumar; Yuke Zhu (ICRA, 2021)

Dynamics Randomization Revisited: A Case Study for Quadrupedal Locomotion. - Zhaoming Xie; Xingye Da; Michiel van de Panne; Buck Babich; Animesh Garg (ICRA, 2021)

Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos. - Haoyu Xiong; Quanzhou Li; Yun-Chun Chen; Homanga Bharadhwaj; Samarth Sinha; Animesh Garg (IROS, 2021)

Dynamic Bottleneck for Robust Self-Supervised Exploration. - Chenjia Bai; Lingxiao Wang 003; Lei Han 001; Animesh Garg; Jianye Hao; Peng Liu 008; Zhaoran Wang 001 (NeurIPS, 2021)

Real Robot Challenge: A Robotics Competition in the Cloud. - Stefan Bauer; Manuel Wüthrich; Felix Widmaier; Annika Buchholz; Sebastian Stark; Anirudh Goyal; Thomas Steinbrenner; Joel Akpo; Shruti Joshi; Vincent Berenz; Vaibhav Agrawal; Niklas Funk; et al. (NeurIPS (Competition and Demos), 2021)

Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers. - Nikita Dvornik; Isma Hadji; Konstantinos G. Derpanis; Animesh Garg; Allan D. Jepson (NeurIPS, 2021)

Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions. - Michael Poli; Stefano Massaroli; Luca Scimeca; Sanghyuk Chun; Seong Joon Oh; Atsushi Yamashita; Hajime Asama; Jinkyoo Park; Animesh Garg (NeurIPS, 2021)

DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting. - Eric Heiden; Miles Macklin; Yashraj S. Narang; Dieter Fox; Animesh Garg; Fabio Ramos 001 (Robotics: Science and Systems, 2021)

Robust Value Iteration for Continuous Control Tasks. - Michael Lutter; Shie Mannor; Jan Peters 001; Dieter Fox; Animesh Garg (Robotics: Science and Systems, 2021)

GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels. - Dylan Turpin; Liquan Wang; Stavros Tsogkas; Sven J. Dickinson; Animesh Garg (Robotics: Science and Systems, 2021)

S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning. - Samarth Sinha; Animesh Garg (CoRR, 2021)

A Robot Cluster for Reproducible Research in Dexterous Manipulation. - Stefan Bauer; Felix Widmaier; Manuel Wüthrich; Niklas Funk; Julen Urain De Jesus; Jan Peters 001; Joe Watson; Claire Chen; Krishnan Srinivasan; Junwu Zhang; Jeffrey Zhang 005; Matthew R. Walter; et al. (CoRR, 2021)

Auditing AI models for Verified Deployment under Semantic Specifications. - Homanga Bharadhwaj; De-An Huang; Chaowei Xiao; Anima Anandkumar; Animesh Garg (CoRR, 2021)

Reinforcement Learning in Factored Action Spaces using Tensor Decompositions. - Anuj Mahajan; Mikayel Samvelyan; Lei Mao; Viktor Makoviychuk; Animesh Garg; Jean Kossaifi; Shimon Whiteson; Yuke Zhu; Animashree Anandkumar (CoRR, 2021)

Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings. - Matthew Shunshi Zhang; Murat A. Erdogdu; Animesh Garg (AAAI, 2022)

Centralized Model and Exploration Policy for Multi-Agent RL. - Qizhen Zhang 002; Christopher Lu 001; Animesh Garg; Jakob N. Foerster (AAMAS, 2022)

Bayesian Object Models for Robotic Interaction with Differentiable Probabilistic Programming. - Krishna Murthy Jatavallabhula; Miles Macklin; Dieter Fox; Animesh Garg; Fabio Ramos 001 (CoRL, 2022)

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 (CoRL, 2022)

Neural Shape Mating: Self-Supervised Object Assembly with Adversarial Shape Priors. - Yun-Chun Chen; Haoda Li; Dylan Turpin; Alec Jacobson; Animesh Garg (CVPR, 2022)

X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval. - Satya Krishna Gorti; Noël Vouitsis; Junwei Ma; Keyvan Golestan; Maksims Volkovs; Animesh Garg; Guangwei Yu (CVPR, 2022)

Uniform Priors for Data-Efficient Learning. - Samarth Sinha; Karsten Roth; Anirudh Goyal; Marzyeh Ghassemi; Zeynep Akata; Hugo Larochelle; Animesh Garg (CVPR Workshops, 2022)

Modular Action Concept Grounding in Semantic Video Prediction. - Wei Yu; Wenxin Chen; Songheng Yin; Steve Easterbrook; Animesh Garg (CVPR, 2022)

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 (ECCV (6), 2022)

Accelerated Policy Learning with Parallel Differentiable Simulation. - Jie Xu 028; Viktor Makoviychuk; Yashraj S. Narang; Fabio Ramos 001; Wojciech Matusik; Animesh Garg; Miles Macklin (ICLR, 2022)

Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning. - Chenjia Bai; Lingxiao Wang 003; Zhuoran Yang; Zhi-Hong Deng; Animesh Garg; Peng Liu 008; Zhaoran Wang 001 (ICLR, 2022)

Value Gradient weighted Model-Based Reinforcement Learning. - Claas Voelcker; Victor Liao; Animesh Garg; Amir-massoud Farahmand (ICLR, 2022)

Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. - Matthias Weissenbacher; Samarth Sinha; Animesh Garg; Yoshinobu Kawahara (ICML, 2022)

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 Wüthrich; Stefan Bauer; Ankur Handa; Animesh Garg (IROS, 2022)

Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation. - Mayank Mittal; David Hoeller; Farbod Farshidian; Marco Hutter 001; Animesh Garg (IROS, 2022)

Experience Replay with Likelihood-free Importance Weights. - Samarth Sinha; Jiaming Song; Animesh Garg; Stefano Ermon (L4DC, 2022)

MoCoDA: Model-based Counterfactual Data Augmentation. - Silviu Pitis; Elliot Creager; Ajay Mandlekar; Animesh Garg (NeurIPS, 2022)

Breaking Bad: A Dataset for Geometric Fracture and Reassembly. - Silvia Sellán; Yun-Chun Chen; Ziyi Wu; Animesh Garg; Alec Jacobson (NeurIPS, 2022)

SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments. - Mohan Zhang; Xiaozhou Wang; Benjamin Decardi-Nelson; Bo Song; An Zhang 007; Jinfeng Liu 001; Sile Tao; Jiayi Cheng; Xiaohong Liu 001; Dengdeng Yu; Matthew Poon; Animesh Garg (NeurIPS, 2022)

GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model. - Zhaoming Xie; Xingye Da; Buck Babich; Animesh Garg; Michiel van de Panne (WAFR, 2022)

Learning latent actions to control assistive robots. - Dylan P. Losey; Hong Jun Jeon; Mengxi Li; Krishnan Srinivasan; Ajay Mandlekar; Animesh Garg; Jeannette Bohg; Dorsa Sadigh (Auton. Robots, 2022)

X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval. - Satya Krishna Gorti; Noël Vouitsis; Junwei Ma; Keyvan Golestan; Maksims Volkovs; Animesh Garg; Guang Wei Yu (CoRR, 2022)

Neural Motion Fields: Encoding Grasp Trajectories as Implicit Value Functions. - Yun-Chun Chen; Adithyavairavan Murali; Balakumar Sundaralingam; Wei Yang 019; Animesh Garg; Dieter Fox (CoRR, 2022)

See, Plan, Predict: Language-guided Cognitive Planning with Video Prediction. - Maria Attarian; Advaya Gupta; Ziyi Zhou; Wei Yu; Igor Gilitschenski; Animesh Garg (CoRR, 2022)

NeurIPS 2022 Competition: Driving SMARTS. - 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; et al. (CoRR, 2022)

An Adaptive Robotics Framework for Chemistry Lab Automation. - Naruki Yoshikawa; Andrew Zou Li; Kourosh Darvish; Yuchi Zhao; Haoping Xu; Alán Aspuru-Guzik; Animesh Garg; Florian Shkurti (CoRR, 2022)

Offline Policy Optimization in RL with Variance Regularizaton. - Riashat Islam; Samarth Sinha; Homanga Bharadhwaj; Samin Yeasar Arnob; Zhuoran Yang; Animesh Garg; Zhaoran Wang 001; Lihong Li; Doina Precup (CoRR, 2022)

Unsupervised Disentanglement of Pose, Appearance and Background from Images and Videos. - Aysegul Dundar; Kevin J. Shih; Animesh Garg; Robert Pottorf; Andrew Tao; Bryan Catanzaro (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

PlaTe: Visually-Grounded Planning With Transformers in Procedural Tasks. - Jiankai Sun; De-An Huang; Bo Lu; Yun-Hui Liu 001; Bolei Zhou; Animesh Garg (IEEE Robotics Autom. Lett., 2022)

Geometry Matching for Multi-Embodiment Grasping. - Maria Attarian; Muhammad Adil Asif; Jingzhou Liu; Ruthrash Hari; Animesh Garg; Igor Gilitschenski; Jonathan Tompson (CoRL, 2023)

Composable Part-Based Manipulation. - Weiyu Liu; Jiayuan Mao; Joy Hsu; Tucker Hermans; Animesh Garg; Jiajun Wu 001 (CoRL, 2023)

SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models. - Ziyi Wu; Nikita Dvornik; Klaus Greff; Thomas Kipf; Animesh Garg (ICLR, 2023)

Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward. - Zihan Zhou; Animesh Garg (ICLR, 2023)

nerf2nerf: Pairwise Registration of Neural Radiance Fields. - Lily Goli; Daniel Rebain; Sara Sabour; Animesh Garg; Andrea Tagliasacchi (ICRA, 2023)

ProgPrompt: Generating Situated Robot Task Plans using Large Language Models. - Ishika Singh; Valts Blukis; Arsalan Mousavian; Ankit Goyal 001; Danfei Xu; Jonathan Tremblay; Dieter Fox; Jesse Thomason; Animesh Garg (ICRA, 2023)

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 (ICRA, 2023)

Self-Supervised Learning of Action Affordances as Interaction Modes. - Liquan Wang; Nikita Dvornik; Rafael Dubeau; Mayank Mittal; Animesh Garg (ICRA, 2023)

MVTrans: Multi-View Perception of Transparent Objects. - Yi Ru Wang; Yuchi Zhao; Haoping Xu; Sagi Eppel; Alán Aspuru-Guzik; Florian Shkurti; Animesh Garg (ICRA, 2023)

SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models. - Ziyi Wu; Jingyu Hu; Wuyue Lu 002; Igor Gilitschenski; Animesh Garg (NeurIPS, 2023)

ORBIT: A Unified Simulation Framework for Interactive Robot Learning Environments. - 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; et al. (CoRR, 2023)

Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting. - Marta Skreta; Naruki Yoshikawa; Sebastian Arellano-Rubach; Zhi Ji; Lasse Bjørn Kristensen; Kourosh Darvish; Alán Aspuru-Guzik; Florian Shkurti; Animesh Garg (CoRR, 2023)

Δ-Networks for Efficient Model Patching. - Chaitanya Devaguptapu; Samarth Sinha; K. J. Joseph; Vineeth N. Balasubramanian; Animesh Garg (CoRR, 2023)

StepFormer: Self-supervised Step Discovery and Localization in Instructional Videos. - Nikita Dvornik; Isma Hadji; Ran Zhang; Konstantinos G. Derpanis; Animesh Garg; Richard P. Wildes; Allan D. Jepson (CoRR, 2023)

Fast-Grasp'D: Dexterous Multi-finger Grasp Generation Through Differentiable Simulation. - Dylan Turpin; Tao Zhong; Shutong Zhang; Guanglei Zhu; Jingzhou Liu; Ritvik Singh; Eric Heiden; Miles Macklin; Stavros Tsogkas; Sven J. Dickinson; Animesh Garg (CoRR, 2023)

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 (CoRR, 2023)

Robot-Assisted Vascular Shunt Insertion with the dVRK Surgical Robot. - Karthik Dharmarajan; Will Panitch; Baiyu Shi; Huang Huang; Lawrence Yunliang Chen; Masoud Moghani; Qinxi Yu; Kush Hari; Thomas Low; Danyal Fer; Animesh Garg; Ken Goldberg (J. Medical Robotics Res., 2023)

Benchmarks for Physical Reasoning AI. - Andrew Melnik; Robin Schiewer; Moritz Lange; Andrei Ioan Muresanu; Mozhgan Saeidi; Animesh Garg; Helge J. Ritter (Trans. Mach. Learn. Res., 2023)

Continuous-Time Fitted Value Iteration for Robust Policies. - Michael Lutter; Boris Belousov; Shie Mannor; Dieter Fox; Animesh Garg; Jan Peters 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

DiSECt: a differentiable simulator for parameter inference and control in robotic cutting. - Eric Heiden; Miles Macklin; Yashraj S. Narang; Dieter Fox; Animesh Garg; Fabio Ramos 001 (Auton. Robots, 2023)

Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments. - 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; et al. (IEEE Robotics Autom. Lett., 2023)

ProgPrompt: program generation for situated robot task planning using large language models. - Ishika Singh; Valts Blukis; Arsalan Mousavian; Ankit Goyal 001; Danfei Xu; Jonathan Tremblay; Dieter Fox; Jesse Thomason; Animesh Garg (Auton. Robots, 2023)

Large language models for chemistry robotics. - Naruki Yoshikawa; Marta Skreta; Kourosh Darvish; Sebastian Arellano-Rubach; Zhi Ji; Lasse Bjørn Kristensen; Andrew Zou Li; Yuchi Zhao; Haoping Xu; Artur Kuramshin; Alán Aspuru-Guzik; Florian Shkurti; et al. (Auton. Robots, 2023)

Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation. - Ignat Georgiev; Krishnan Srinivasan; Jie Xu; Eric Heiden; Animesh Garg (ICML, 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)

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 (ICRA, 2024)

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 Lin; Miles Macklin; Animesh Garg (ICRA, 2024)

RePLan: Robotic Replanning with Perception and Language Models. - Marta Skreta; Zihan Zhou; Jia Lin Yuan; Kourosh Darvish; Alán Aspuru-Guzik; Animesh Garg (CoRR, 2024)

ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization. - Kourosh Darvish; Marta Skreta; Yuchi Zhao; Naruki Yoshikawa; Sagnik Som; Miroslav Bogdanovic; Yang Cao; Han Hao; Haoping Xu; Alán Aspuru-Guzik; Animesh Garg; Florian Shkurti (CoRR, 2024)

Fast Explicit-Input Assistance for Teleoperation in Clutter. - Nick Walker 001; Xuning Yang; Animesh Garg; Maya Cakmak; Dieter Fox; Claudia Pérez-D'Arpino (CoRR, 2024)

Multi-Constraint Safe RL with Objective Suppression for Safety-Critical Applications. - Zihan Zhou; Jonathan Booher; Wei Liu; Aleksandr Petiushko; Animesh Garg (CoRR, 2024)

AdaDemo: Data-Efficient Demonstration Expansion for Generalist Robotic Agent. - Tongzhou Mu; Yijie Guo; Jie Xu 028; Ankit Goyal 001; Hao Su 001; Dieter Fox; Animesh Garg (CoRR, 2024)

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 (CoRR, 2024)

PWM: Policy Learning with Large World Models. - Ignat Georgiev; Varun Giridhar; Nicklas Hansen 001; Animesh Garg (CoRR, 2024)

QueST: Self-Supervised Skill Abstractions for Learning Continuous Control. - Atharva Mete; Haotian Xue; Albert Wilcox; Yongxin Chen; Animesh Garg (CoRR, 2024)

Monotonic Quantile Network for Worst-Case Offline Reinforcement Learning. - Chenjia Bai; Ting Xiao; Zhoufan Zhu; Lingxiao Wang 003; Fan Zhou; Animesh Garg; Bin He 003; Peng Liu 008; Zhaoran Wang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)