For the up-to-date publication list, please see Google Scholar or Semantic Scholar pages.

Preprints

  1. GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model. Zhaoming Xie, Xingye Da, Buck Babich, Animesh Garg, Michiel van de Panne. preprint 2021 Model-Free RL in centroidal model for desired body accelerations with subsequent computation of ground reaction forces using a robot model. arXiv project
  2. S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning. Samrath Sinha, Animesh Garg. preprint 2021 Data-augmentation with simple perturbations improve robustness, generalization, and OOD performance in Offline RL arXiv
  3. Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation. Mayank Mittal, David Hoeller, Farbod Farshidian, Marco Hutter, Animesh Garg. preprint 2021 Predict expected keyframes of operating an articulated object, then plan for close-loop dyanmically-feasible whole-body motion to match predicted object trajectory. arXiv project
  4. Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos. Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samrath Sinha, Animesh Garg. preprint 2021 Style transfer human videos to robot perspective, then sparse unsupervised keypoints for reward estimation, use RL for model-free task completion. arXiv project video
  5. Concept Grounding with Modular Action-Capsules in Semantic Video Prediction. Wei Yu, Wenxin Chen, Songheng Yin, Steve Easterbrook, Animesh Garg. preprint 2020 Object-Oriented semantic manipulation of scenes with unsupervised capsule networks which learn grounding of both objects and actions. arXiv project
  6. D2RL: Deep Dense Architectures in Reinforcement Learning. Samarth Sinha, Homanga Bharadhwaj, Aravind Srinivas, Animesh Garg. preprint 2020 Architectures in RL do not need to be simple MLPs! Dense connections in both actor and critic improve representation learning and hence performance. arXiv project code
  7. De-anonymization of authors through arXiv submissions during double-blind review. Homanga Bharadhwaj, Dylan Turpin, Animesh Garg, Ashton Anderson. preprint 2020 Doubt-blind reviewing process may tilt the scales in favor of eminent authors who de-anonymize through concurrent arxiv release. arXiv blog
  8. Experience Replay with Likelihood-free Importance Weights. Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon. preprint 2020 arXiv
  9. Uniform Priors for Data-Efficient Transfer. Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Hugo Larochelle, Animesh Garg. preprint 2020 arXiv

Papers (Journals & Conferences)

  1. LASER: Learning a Latent Action Space for Efficient Reinforcement Learning. Arthur Allshire, Roberto Martin-Martin, Charles Lin, Shawn Mendes, Silvio Savarese, Animesh Garg. IEEE International Conference on Robotics and Automation (ICRA) 2021 Learn a lower dimensional action-space that results in efficient exploration in similar tasks. arXiv project video
  2. Dynamics Randomization Revisited: A Case Study for Quadrupedal Locomotion. Zhaoming Xie, Xingye Da, Michiel van de Panne, Buck Babich, Animesh Garg. IEEE International Conference on Robotics and Automation (ICRA) 2021 Dynamics randomization is neither necessary nor sufficient for sim-to-real transfer of learning robust locomotion policies. arXiv project
  3. LEAF: Latent Exploration Along the Frontier. Homanga Bharadhwaj, Animesh Garg, Florian Shkurti. IEEE International Conference on Robotics and Automation (ICRA) 2021 Learn a dynamics aware manifold of reachable states, and then use this for guided exploration in hard continuous control tasks with RL. arXiv project
  4. Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects. Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu. IEEE International Conference on Robotics and Automation (ICRA) 2021 A data-driven bayesian optimization approach to jointly optimize hand-design along with policy for grasping diverse objects in multiple modes. arXiv project
  5. Skill Transfer via Partially Amortized Hierarchical Planning. Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti. International Conference on Learning Representations (ICLR) 2021 Combine benefits of learned world-model with a set of modular skills for faster online test-time adaptation. Use learned skills during planning stage improves both speed and data efficiency arXiv project
  6. 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. International Conference on Learning Representations (ICLR) 2021 Horizon-Aware policies trade off safety and perforamce while encoding multimodal solutions. Insight is to learn cumulative accessibility C(s,a,h) with time horizon h instead of the usual Q-function Q(s,a). arXiv project
  7. Conservative Safety Critics for Exploration. Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg. International Conference on Learning Representations (ICLR) 2021 We need to guarantee safety during training in RL. Instead of unintuitive specification of state based safety, we can learn safety as a separate value function, and can jointly optimize for task performance with safety value as a constraint. arXiv project talk
  8. DIBS: Diversity inducing Information Bottleneck in Model Ensembles. Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti. Confernce on Artificial Intelligence (AAAI) 2021 Ensembles of deep nets to model uncertianty in modeling multi-modal data by encouraging diversity in prediction through adversarial loss for learning the stochastic latent variables arXiv
  9. Unsupervised Disentanglement of Pose, Appearance and Background from Images and Videos. Aysegul Dundar, Kevin J. Shih, Animesh Garg, Robert Pottorf, Andrew Tao, Bryan Catanzaro. Transactions on Pattern Analysis and Machine Intelligence (T-PAMI) 2021 arXiv code
  10. Causal Discovery in Physical Systems from Videos. Yunzhu Li, Antonio Torralba, Animashree Anandkumar, Dieter Fox, Animesh Garg. Advances in Neural Information Processing Systems 33 (NeurIPS) 2020 Learn the underlying generative model as a causal graph with a few frames of observation. Generalize across variable latent dynamics (both graph connectivity and parameters). arXiv project
  11. Curriculum By Smoothing. Samarth Sinha, Animesh Garg, Hugo Larochelle. Advances in Neural Information Processing Systems 33 (NeurIPS) 2020 Curriculum deisgn to improve representation learning in CNN by restricting access to high frequency information until later in the training NeurIPS 2020 (Spotlight)
    arXiv
  12. Counterfactual Data Augmentation using Locally Factored Dynamics. Silviu Pitis, Elliot Creager, Animesh Garg. Advances in Neural Information Processing Systems 33 (NeurIPS) 2020 Outstanding Paper Award at Object-Oriented Learning (OOL) Workshop, ICML 2020
    arXiv code talk
  13. Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion. Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Animashree Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg. Conference on Robot Learning (CoRL) 2020 arXiv blog video
  14. 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 Saverese. IEEE International Conference on Intelligent Robots and Systems (IROS) 2020 arXiv project talk
  15. A Programmable Approach to Neural Network Compression. Vinu Joseph, Ganesh Gopalakrishnan, Saurav Muralidharan, Michael Garland, Animesh Garg. IEEE Micro 2020 Demystifying network compression: user inputs pretrained model, compression scheme, objective and constraints. Condensa uses bayesian optimization to infer optimal sparsity ratio and corresponding compressed model. arXiv pdf project code
  16. Ocean: Online Task Inference for Compositional Tasks with Context Adaptation. Hongyu Ren, Yuke Zhu, Jure Leskovec, Anima Anandkumar, Animesh Garg. Conference on Uncertainty in Artificial Intelligence (UAI) 2020 A hierarchical latent variable prior that goes beyond vanilla gaussians to capture global and local context in sequential decision making for Meta-RL. arXiv pdf supp code talk
  17. Semi-Supervised StyleGAN for Disentanglement Learning. Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debhath, Anjul Patney, Ankit B. Patel, Anima Anandkumar. International Conference on Machine Learning (ICML) 2020 Dientanglement in GANs with 0.25-2.5% labelled dataset for high-resolution fine-grained control over image generation. arXiv project code slides talk
  18. Angular Visual Hardness. Beidi Chen, Weiyang Liu, Animesh Garg, Zhiding Yu, Anshumali Shrivastava, Jan Kautz, Anima Anandkumar. International Conference on Machine Learning (ICML) 2020 Normalized angular distance between the sample feature embedding and the target classifier to measure sample hardness. arXiv project slides talk
  19. 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. IEEE International Conference on Robotics and Automation (ICRA) 2020 Offline demonstrations are both suboptimal and multimodal. Use two-stage model-learning: a high leven generative model to fit multi-modal state density, and a low-level imitation model for near optimal control. arXiv project video talk
  20. Combining Model-Free and Model-Based Strategies for Sample-Efficient Reinforcement Learning. Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, Nathan Ratliff, Animesh Garg, Fabio Ramos, Dieter Fox. IEEE International Conference on Robotics and Automation (ICRA) 2020 Best Paper Award at 2019 Neurips Workshop on Robot Learning
    arXiv video talk
  21. 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. IEEE International Conference on Robotics and Automation (ICRA) 2020 Combine task & motion planning to disambiguate the true intention of the demonstrator from video where they performed multiple subtasks but only a subset was relevant to true objective, others were constraint satisfaction. arXiv video
  22. Controlling Assistive Robots with Learned Latent Actions. Dylan P. Losey, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Dorsa Sadigh. IEEE International Conference on Robotics and Automation (ICRA) 2020 Learn a action space encoding from expert demonstrations, align the encoding with lower-dimension controller to enable efficient teleoperation. arXiv blog video talk
  23. 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, Animesh Garg, Jeannette Bohg. IEEE Transactions on Robotics (T-RO) 2020 arXiv project
  24. 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. IEEE International Conference on Intelligent Robots and Systems (IROS) 2019 IROS Best Cognitive Robotics Paper Finalist
    arXiv project code blog
  25. 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 Carlos. IEEE International Conference on Intelligent Robots and Systems (IROS) 2019 arXiv video
  26. Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks. Roberto Martı́n-Martı́n, Michelle A Lee, Rachel Gardner, Silvio Savarese, Jeannette Bohg, Animesh Garg. IEEE International Conference on Intelligent Robots and Systems (IROS) 2019 arXiv project
  27. Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation. Kuan Fang, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei. Conference on Robot Learning (CoRL) 2019 Oral Presentation
    arXiv project
  28. AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers. Andrey Kurenkov, Ajay Mandlekar, Roberto Martín-Martín, Silvio Savarese, Animesh Garg. Conference on Robot Learning (CoRL) 2019 arXiv project code blog
  29. Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision. Kuan Fang, Yuke Zhu, Animesh Garg, Andrey Kurenkov, Viraj Mehta, Li Fei-Fei, Silvio Savarese. International Journal of Robotics Research (IJRR) 2019 pdf project video
  30. 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. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 Oral Presentation
    arXiv video
  31. Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter. Mike Danielczuk, Andrey Kurenkov, Ashwin Balakrishna, Matthew Matl, Roberto Martín-Martín, Animesh Garg, Silvio Savarese, Ken Goldberg. IEEE International Conference on Robotics and Automation (ICRA) 2019 abstract arXiv project video
  32. 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 (* equal contribution). IEEE International Conference on Robotics and Automation (ICRA) 2019 ICRA Best Paper Award and Finalist: Best Cognitive Robotics Paper
    arXiv project video
  33. 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. Conference on Robot Learning (CoRL) 2018 arXiv pdf project code blog talk
  34. 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. International Journal of Robotics Research (IJRR) 2018 pdf project
  35. Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision. Kuan Fang, Yuke Zhu, Animesh Garg, Andrey Kurenkov, Viraj Mehta, Li Fei-Fei, Silvio Savarese. Robotics: Systems and Science (RSS) 2018 arXiv project video talk
  36. Finding It: Weakly-Supervised Reference-Aware Visual Grounding in Instructional Video. De-An Huang, Shyamal Buch, Lucio Dery, Animesh Garg, Li Fei-Fei, Juan Carlos Niebles. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 Oral Presentation
    pdf supp project poster talk
  37. Neural Task Programming: Learning to generalize across hierarchical tasks. Danfei Xu, Suraj Nair, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, Silvio Savarese. IEEE International Conference on Robotics and Automation (ICRA) 2018 arXiv project video talk
  38. DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image. Andrey Kurenkov*, Jingwei Ji*, Animesh Garg, Viraj Mehta, JunYoung Gwak, Christopher Choy, Silvio Savarese (* equal contribution). IEEE Winter Conference on Applications of Computer Vision (WACV) 2018 arXiv project talk
  39. 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 (* equal contribution). International Symposium on Robotics Research (ISRR) 2017 arXiv
  40. Transition State Clustering: Unsupervised surgical trajectory segmentation for robot learning. Sanjay Krishnan*, Animesh Garg*, Sachin Patil, Colin Lea, Gregory Hager, Pieter Abbeel, Ken Goldberg (* equal contribution). International Journal of Robotics Research (IJRR) 2017 pdf code
  41. Weakly Supervised Generative Adversarial Networks for 3D Reconstruction. JunYoung Gwak*, Christopher B Choy*, Animesh Garg, Manmohan Chandraker, Silvio Savarese (* equal contribution). IEEE Conference on 3D Vision (3DV) 2017 arXiv code
  42. Adversarially Robust Policy Learning through Active Construction of Physically-Plausible Perturbations. Ajay Mandlekar*, Yuke Zhu*, Animesh Garg*, Li Fei-Fei, Silvio Savarese (* equal contribution). IEEE International Conference on Intelligent Robots and Systems (IROS) 2017 pdf project video
  43. 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. IEEE International Conference on Robotics and Automation (ICRA) 2017 pdf video
  44. 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. Workshop on Algorithmic Foundations of Robotics (WAFR) 2016 pdf talk
  45. Interchangeable Surgical Instrument System with Application to Supervised Automation of Multilateral Tumor Resection. . Stephen McKinley, Animesh Garg, Siddarth Sen, David V. Gealy, Jonathan McKinley, Yiming Jen, Menglung Guo, Doug Boyd, Ken Goldberg. IEEE International Conference on Automation Science & Engg. (CASE) 2016 Best Video Award at 2015 Hamlyn Symposium
    project video
  46. Autonomous Multiple-Throw Multilateral Surgical Suturing with a Mechanical Needle Guide and Optimization based Needle Planning . Siddarth Sen*, Animesh Garg*, David Gealy, Stephen McKinley, Yiming Jen, Ken Goldberg (* equal contribution). IEEE International Conference on Robotics & Automation (ICRA) 2016 project video
  47. TSC-DL: Unsupervised Trajectory Segmentation of Multi-Modal Surgical Demonstrations with Deep Learning . Adithyavairavan Murali*, Animesh Garg*, Sanjay Krishnan*, Florian Pokorny, Pieter Abbeel, Trevor Darrell, Ken Goldberg (* equal contribution). IEEE International Conference on Robotics & Automation (ICRA) 2016 project code video
  48. Tumor localization using automated palpation with Gaussian Process Adaptive Sampling. Animesh Garg, Siddarth Sen, Rishi Kapadia, Yiming Jen, Stephen McKinley, Lauren Miller, Ken Goldberg. IEEE International Conference on Automation Science & Engg. (CASE) 2016 pdf project
  49. 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 Nichols, Susan Lim, Sachin Patil, Pieter Abbeel, Allison M. Okamura, Ken Goldberg. IEEE International Conference on Automation Science & Engg. (CASE) 2015 Best Poster/Demo Award at ICRA 2015 Workshop on Shared Frameworks for Medical Robotics
    abstract pdf project
  50. 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, Ken Goldberg. IEEE International Conference on Robotics & Automation (ICRA) 2015 Finalist: Best Paper, Student Paper, and Medical Robotics Paper Award
    abstract project video
  51. Material Evaluation of PC-ISO for Customized, 3D Printed, Gynecologic 192Ir HDR Brachytherapy Applicators. Katherine Mellis, Timmy Siauw, Atchar Sudhyadhom, Rajni Sethi, I-Chow Hsu, Jean Pouliot, Animesh Garg, Ken Goldberg. Journal of Applied Clinical Medical Physics (JACMP) 2015 project
  52. Transition State Clustering: Unsupervised Surgical Trajectory Segmentation For Robot Learning. Sanjay Krishnan*, Animesh Garg*, Sachin Patil, Colin Lea, Gregory Hager, Pieter Abbeel, Ken Goldberg (* equal contribution). International Symposium on Robotics Research (ISRR) 2015 code
  53. 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, Ken Goldberg. IEEE International Conference on Automation Science & Engg. (CASE) 2014 abstract project
  54. Customized Needle Guides for Inserting Non-Parallel Needle Arrangements in Prostate HDR Brachytherapy: A Phantom Study. Timmy Siauw, J. Adam M. Cunha, Animesh Garg, Ken Goldberg, I Hsu, Jean Pouliot. Brachytherapy 2014 project
  55. 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-C Hsu, Jean Pouliot, Dan Stoianovici, Ken Goldberg. IEEE Transactions on Automation Science and Engineering (T-ASE) 2013 abstract pdf
  56. 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 Hsu, Pieter Abbeel, Jean Pouliot, Ken Goldberg. IEEE International Conference on Automation Science & Engg. (CASE) 2013 abstract pdf project
  57. Initial experiments toward automated robotic implantation of skew-line needle arrangements for HDR brachytherapy. A. Garg, T. Siauw, D. Berenson, A. Cunha, I-Chow Hsu, J. Pouliot, D. Stoianovici, K. Goldberg. IEEE International Conference on Automation Science & Engg. (CASE) 2012 IEEE CASE Best Application Paper Award
    abstract project video talk
  58. Robotic Brachytherapy Demonstration: Implant of HDR Brachytherapy Needle Configuration Computer-Optimized to Avoid Critical Structures Near the Bulb of the Penis. JA Cunha, T Siauw, A Garg, N Zhang, K Goldberg, D Stoianovici, M Roach III, I-C Hsu, J Pouliot. Medical Physics 2012 pdf
  59. Robot-guided Delivery of Brachytherapy Needles along Non-Parallel Paths to Avoid Penile Bulb Puncture. JAM Cunha, A Garg, T Siauw, N Zhang, Y Zuo, K Goldberg, D Stoianovici, M Roach III, J Pouliot. Radiotherapy and Oncology 2012 pdf
  60. Low-Cost Teleoperation of Remotely Located Actuators Based on Dual Tone Multi-Frequency Data Transfer. Sahil Thakkar, Animesh Garg, Adesh Midha, Prerna Gaur. MEMS, NANO and Smart Systems 2012 abstract pdf
  61. The Autotrix: Design and Implementation of an Autonomous Urban Driving System. Animesh Garg, Anju Toor, Sahil Thakkar, Shiwangi Goel, Sachin Maheshwari, Satish Chand. MEMS, NANO and Smart Systems 2012 abstract pdf
  62. Object Identification and Mapping using Monocular Vision in an Autonomous Urban Driving System. Animesh Garg, Anju Toor, Sahil Thakkar, Shiwangi Goel, Sachin Maheshwari, Satish Chand. International Conference of Machine Vision 2010

Peer-Reviewed Workshops

  1. Counterfactual Data Augmentation using Locally Factored Dynamics. Silviu Pitis, Elliot Creager, Animesh Garg. Workshop on Object-Oriented Learning (OOL) at ICML 2020 Outstanding Paper Award at Object-Oriented Learning (OOL) Workshop, ICML 2020
    code poster talk
  2. Turbulence forecasting via Neural ODE. Gavin Portwood, Peetak Mitra, Mateus Dias Ribeiro, Tan Minh Nguyen, Balasubramanya Nadiga, Juan Saenz, Micheal Chertkov, Animesh Garg, Anima Anandkumar, Andreas Dengel, Richard Baraniuk, David Schmidt. Workshop on Machine Learning and the Physical Sciences at NeurIPS 2019 pdf
  3. Combining Model-Free and Model-Based Strategies for Sample-Efficient Reinforcement Learning. Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, Nathan Ratliff, Animesh Garg, Fabio Ramos, Dieter Fox. Workshop on Robot Learning at NeurIPS 2019 Best paper award at the workshop
    pdf
  4. Hierarchical Task Generalization with Neural Programs. Danfei Xu, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, Silvio Savarese. Conference on Robot Learning (CoRL), workshop track 2017 talk
  5. Towards Grasp Transfer using Shape Deformation.. Andrey Kuyenkov*, Viraj Mehta*, Jingwei Ji, Animesh Garg, Silvio Savarese (* equal contribution). Conference on Robot Learning (CoRL), workshop track 2017 pdf poster
  6. Hierarchical Task Generalization with Neural Programs. Danfei Xu, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, Silvio Savarese. R:SS Workshop on New Frontiers for Deep Learning in Robotics 2017 poster
  7. Adversarially Robust Policy Learning through Active Construction of Physically-Plausible Perturbations. Ajay Mandlekar*, Yuke Zhu*, Animesh Garg*, Li Fei-Fei, Silvio Savarese (* equal contribution). Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) 2017 pdf
  8. 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. 2016 arXiv
  9. On Visual Feature Representations for Transition State Learning in Robotic Task Demonstrations. Animesh Garg*, Sanjay Krishnan*, Adithyavairavan Murali, Trevor Darrell, Pieter Abbeel, Ken Goldberg (* equal contribution). NIPS Workshop on Feature Extraction 2015 pdf project
  10. Automated Delivery Instrument for Stem Cell Treatment Using the daVinci Robotic Surgical System. Stephen McKinley, Animesh Garg, Susan Lim, Sachin Patil, Ken Goldberg. Annual Meeting of the International Society for Stem Cell Research. Stockholm, Sweden. 2015 poster
  11. Autonomous Tumor Localization and Extraction: Palpation, Incision, Debridement and Adhesive Closure with the da Vinci Research Kit. Stephen McKinley, Siddarth Sen, Animesh Garg, Yiming Jen, David Gealy, Pieter Abbeel, Ken Goldberg. Hamlyn Surgical Robotics Conference, London 2015 Best Video Award
    video

Theses

Patents

  1. Precision injector/extractor for robot-assisted minimally-invasive surgery. Stephen Mckinley, Animesh Garg, Sachin Patil, Susan ML Lim, Ken Goldberg. U.S. Provisional. PCT International Application No.: PCT/US2016/039,026, June, 2016 project
  2. Patient-Specific Temporary Implants For Accurately Guiding Local Means of Tumor Control Along Patient-Specific Internal Channels to Treat Cancers. Jean Pouliot, I-Chow Ken Goldberg, J. Adam Cunha, Animesh Garg, Sachin Patil, Pieter Abbeel, Timmy Siauw. US Patent 10,286,197, May, 2019 project

Technical Reports

  1. Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors. Tim Barfoot, Jessica Burgner-Kahrs, Eric Diller, Animesh Garg, Andrew Goldenberg, Jonathan Kelly, Xinyu Liu, Hani E. Naguib, Goldie Nejat, Angela P. Schoellig, Florian Shkurti, Hallie Siegel, Yu Sun, Steven Waslander. 2020 arXiv blog
  2. InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers. Tan M. Nguyen, Animesh Garg, Richard G. Baraniuk, Anima Anandkumar. 2019 arXiv
  3. Video Interpolation and Prediction with Unsupervised Landmarks. Kevin J. Shih, Aysegul Dundar, Animesh Garg, Robert Pottorf, Andrew Tao, Bryan Catanzaro. 2019 arXiv
  4. Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning. Richard Liaw, Sanjay Krishnan, Animesh Garg, Daniel Crankshaw, Joseph E Gonzalez, Ken Goldberg. 2017 arXiv
  5. Autonomous localization and navigation using 2D laser scanners. Manohar Paluri, Animesh Garg, Henrik Christensen. 2010