Pieter Abbeel

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings

Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel

VideoGPT: Video Generation using VQ-VAE and Transformers

Wilson Yan, Yunzhi Zhang, Pieter Abbeel, Aravind Srinivas

Comments Project website: https://wilson1yan.github.io/videogpt/index.html

APS: Active Pretraining with Successor Features

Hao Liu, Pieter Abbeel

Comments Appeared in ICML 2021

Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback

Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin

Comments 8 pages,6 figures. for associated code and video, see http://sites.google.com/view/skill-pref

Bottleneck Transformers for Visual Recognition

Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani

Comments Technical Report, 20 pages, 13 figures, 19 tables

Playful Interactions for Representation Learning

Sarah Young, Jyothish Pari, Pieter Abbeel, Lerrel Pinto

The MineRL BASALT Competition on Learning from Human Feedback

Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William Guss, Sharada Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca Dragan

Comments NeurIPS 2021 Competition Track

Pretrained Transformers as Universal Computation Engines

Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch

Decision Transformer: Reinforcement Learning via Sequence Modeling

Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch

Comments First two authors contributed equally. Last two authors advised equally

State Entropy Maximization with Random Encoders for Efficient Exploration

Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee

Comments ICML 2021. First two authors contributed equally. Website: https://sites.google.com/view/re3-rl Code: https://github.com/younggyoseo/RE3

Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL

Catherine Cang, Aravind Rajeswaran, Pieter Abbeel, Michael Laskin

Reset-Free Lifelong Learning with Skill-Space Planning

Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch

Comments In the proceedings of the 7th International Conference on Learning Representations (ICLR), Virtual, April 2021

Parallel Training of Deep Networks with Local Updates

Michael Laskin, Luke Metz, Seth Nabarro, Mark Saroufim, Badreddine Noune, Carlo Luschi, Jascha Sohl-Dickstein, Pieter Abbeel

Comments First two authors - Michael Laskin and Luke Metz - contributed equally. Order was determined by a coin flip

Unsupervised Learning of Visual 3D Keypoints for Control

Boyuan Chen, Pieter Abbeel, Deepak Pathak

Comments Accepted at ICML 2021. Videos and code at https://buoyancy99.github.io/unsup-3d-keypoints/

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel

Comments ICML 2021 camera ready

PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training

Kimin Lee, Laura Smith, Pieter Abbeel

Comments ICML 2021. First two authors contributed equally. Website: https://sites.google.com/view/icml21pebble Code: https://github.com/pokaxpoka/B_Pref

Auto-Tuned Sim-to-Real Transfer

Yuqing Du, Olivia Watkins, Trevor Darrell, Pieter Abbeel, Deepak Pathak

Comments ICRA 2021. First two authors contributed equally. Website at https://yuqingd.github.io/autotuned-sim2real/

Decoupling Representation Learning from Reinforcement Learning

Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin

Comments Improved related works and fixed code hyperlink

Efficient Empowerment Estimation for Unsupervised Stabilization

Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin

Learning What To Do by Simulating the Past

David Lindner, Rohin Shah, Pieter Abbeel, Anca Dragan

Comments Presented at ICLR 2021

Self-Supervised Policy Adaptation during Deployment

Nicklas Hansen, Rishabh Jangir, Yu Sun, Guillem Alenyà, Pieter Abbeel, Alexei A. Efros, Lerrel Pinto, Xiaolong Wang

Comments Website: https://nicklashansen.github.io/PAD/ Code: https://github.com/nicklashansen/policy-adaptation-during-deployment ICLR 2021

GEM: Group Enhanced Model for Learning Dynamical Control Systems

Philippe Hansen-Estruch, Wenling Shang, Lerrel Pinto, Pieter Abbeel, Stas Tiomkin

Comments 14 pages, 8 figures

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis

Ajay Jain, Matthew Tancik, Pieter Abbeel

Comments Project website: https://www.ajayj.com/dietnerf

Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots

Zhongyu Li, Xuxin Cheng, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath

Comments To appear on 2021 International Conference on Robotics and Automation (ICRA 2021)

Mutual Information State Intrinsic Control

Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu

Comments Published in International Conference on Learning Representations (ICLR 2021) as Spotlight (top 5%), Link: https://openreview.net/forum?id=OthEq8I5v1. arXiv admin note: text overlap with arXiv:2002.01963

Task-Agnostic Morphology Evolution

Donald J. Hejna, Pieter Abbeel, Lerrel Pinto

Comments ICLR 2021

AvE: Assistance via Empowerment

Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca Dragan

Comments Final version from NeurIPS 2020 Conference Proceedings

Reinforcement Learning with Latent Flow

Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin

Denoising Diffusion Probabilistic Models

Jonathan Ho, Ajay Jain, Pieter Abbeel

Sparse Graphical Memory for Robust Planning

Scott Emmons, Ajay Jain, Michael Laskin, Thanard Kurutach, Pieter Abbeel, Deepak Pathak

Comments Accepted at NeurIPS 2020. Video and code at https://mishalaskin.github.io/sgm/