Animesh Garg

IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data

Learning from offline task demonstrations is a problem of great interest...
11/13/2019 ∙ by Ajay Mandlekar, et al. ∙ 108 ∙ share

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Motion Reasoning for Goal-Based Imitation Learning

We address goal-based imitation learning, where the aim is to output the...
11/13/2019 ∙ by De-An Huang, et al. ∙ 105 ∙ share

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InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers

Continuous Normalizing Flows (CNFs) have emerged as promising deep gener...
12/09/2019 ∙ by Tan M. Nguyen, et al. ∙ 33 ∙ share

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Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning

Traditional robotic approaches rely on an accurate model of the environm...
05/21/2020 ∙ by Michelle A. Lee, et al. ∙ 33 ∙ share

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Unsupervised Disentanglement of Pose, Appearance and Background from Images and Videos

Unsupervised landmark learning is the task of learning semantic keypoint...
01/26/2020 ∙ by Aysegul Dundar, et al. ∙ 25 ∙ share

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Semi-Supervised StyleGAN for Disentanglement Learning

Disentanglement learning is crucial for obtaining disentangled represent...
03/06/2020 ∙ by Weili Nie, et al. ∙ 23 ∙ share

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A Programmable Approach to Model Compression

Deep neural networks frequently contain far more weights, represented at...
11/06/2019 ∙ by Vinu Joseph, et al. ∙ 14 ∙ share

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Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation

The fundamental challenge of planning for multi-step manipulation is to ...
10/29/2019 ∙ by Kuan Fang, et al. ∙ 10 ∙ share

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Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision

Tool manipulation is vital for facilitating robots to complete challengi...
06/25/2018 ∙ by Kuan Fang, et al. ∙ 8 ∙ share

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AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers

The exploration mechanism used by a Deep Reinforcement Learning (RL) age...
09/09/2019 ∙ by Andrey Kurenkov, et al. ∙ 7 ∙ share

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DIBS: Diversity inducing Information Bottleneck in Model Ensembles

Although deep learning models have achieved state-of-the-art performance...
03/10/2020 ∙ by Samarth Sinha, et al. ∙ 7 ∙ share

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Curriculum By Texture

Convolutional Neural Networks (CNNs) have shown impressive performance i...
03/03/2020 ∙ by Samarth Sinha, et al. ∙ 5 ∙ share

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Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks

Contact-rich manipulation tasks in unstructured environments often requi...
10/24/2018 ∙ by Michelle A. Lee, et al. ∙ 4 ∙ share

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RoboTurk: A Crowdsourcing Platform for Robotic Skill Learning through Imitation

Imitation Learning has empowered recent advances in learning robotic man...
11/07/2018 ∙ by Ajay Mandlekar, et al. ∙ 4 ∙ share

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Continuous Relaxation of Symbolic Planner for One-Shot Imitation Learning

We address one-shot imitation learning, where the goal is to execute a p...
08/16/2019 ∙ by De-An Huang, et al. ∙ 3 ∙ share

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Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration

Our goal is for a robot to execute a previously unseen task based on a s...
07/10/2018 ∙ by De-An Huang, et al. ∙ 2 ∙ share

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Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks

Reinforcement Learning (RL) of contact-rich manipulation tasks has yield...
06/20/2019 ∙ by Roberto Martín-Martín, et al. ∙ 2 ∙ share

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Video Interpolation and Prediction with Unsupervised Landmarks

Prediction and interpolation for long-range video data involves the comp...
09/06/2019 ∙ by Kevin J. Shih, et al. ∙ 1 ∙ share

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Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning

Rather than learning new control policies for each new task, it is possi...
11/04/2017 ∙ by Richard Liaw, et al. ∙ 0 ∙ share

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Neural Task Programming: Learning to Generalize Across Hierarchical Tasks

In this work, we propose a novel robot learning framework called Neural ...
10/04/2017 ∙ by Danfei Xu, et al. ∙ 0 ∙ share

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Weakly supervised 3D Reconstruction with Adversarial Constraint

Supervised 3D reconstruction has witnessed a significant progress throug...
05/31/2017 ∙ by JunYoung Gwak, et al. ∙ 0 ∙ share

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DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image

3D reconstruction from a single image is a key problem in multiple appli...
08/11/2017 ∙ by Andrey Kurenkov, et al. ∙ 0 ∙ share

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Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter

When operating in unstructured environments such as warehouses, homes, a...
03/04/2019 ∙ by Michael Danielczuk, et al. ∙ 0 ∙ share

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Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks

Contact-rich manipulation tasks in unstructured environments often requi...
07/28/2019 ∙ by Michelle A. Lee, et al. ∙ 0 ∙ share

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Controlling Assistive Robots with Learned Latent Actions

Assistive robots enable users with disabilities to perform everyday task...
09/20/2019 ∙ by Dylan P. Losey, et al. ∙ 0 ∙ share

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Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity

Large, richly annotated datasets have accelerated progress in fields suc...
11/11/2019 ∙ by Ajay Mandlekar, et al. ∙ 0 ∙ share

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Dynamics-Aware Latent Space Reachability for Exploration in Temporally-Extended Tasks

Self-supervised goal proposal and reaching is a key component of efficie...
05/21/2020 ∙ by Homanga Bharadhwaj, et al. ∙ 0 ∙ share

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Animesh Garg

Featured Co-authors

Li Fei-Fei

Anima Anandkumar

Silvio Savarese

Dieter Fox

Hugo Larochelle

Byron Boots

Richard G. Baraniuk

Joseph E. Gonzalez

Fabio Ramos

Ken Goldberg

Manmohan Chandraker

IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data

Motion Reasoning for Goal-Based Imitation Learning

InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers

Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning

Unsupervised Disentanglement of Pose, Appearance and Background from Images and Videos

Semi-Supervised StyleGAN for Disentanglement Learning

A Programmable Approach to Model Compression

Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation

Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision

AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers

DIBS: Diversity inducing Information Bottleneck in Model Ensembles

Curriculum By Texture

Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks

RoboTurk: A Crowdsourcing Platform for Robotic Skill Learning through Imitation

Continuous Relaxation of Symbolic Planner for One-Shot Imitation Learning

Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration

Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks

Video Interpolation and Prediction with Unsupervised Landmarks

Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning

Neural Task Programming: Learning to Generalize Across Hierarchical Tasks

Weakly supervised 3D Reconstruction with Adversarial Constraint

DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image

Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter

Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks

Controlling Assistive Robots with Learned Latent Actions

Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity

Dynamics-Aware Latent Space Reachability for Exploration in Temporally-Extended Tasks