Pieter Abbeel

AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control

Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, Angjoo Kanazawa

Zero-Shot Text-Guided Object Generation with Dream Fields

Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole

Comments CVPR 2022. 13 pages. Website: https://ajayj.com/dreamfields

Coarse-to-fine Q-attention with Tree Expansion

Stephen James, Pieter Abbeel

Comments Project page and code: https://sites.google.com/view/q-attention-qte

Imitating, Fast and Slow: Robust learning from demonstrations via decision-time planning

Carl Qi, Pieter Abbeel, Aditya Grover

Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning

Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto

Coarse-to-Fine Q-attention with Learned Path Ranking

Stephen James, Pieter Abbeel

Comments Project page and code: https://sites.google.com/view/q-attention-lpr

Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Design

Kourosh Hakhamaneshi, Marcel Nassar, Mariano Phielipp, Pieter Abbeel, Vladimir Stojanović

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery

Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel

Comments Project website: https://sites.google.com/view/cicrl/

Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions

Alejandro Escontrela, Xue Bin Peng, Wenhao Yu, Tingnan Zhang, Atil Iscen, Ken Goldberg, Pieter Abbeel

Comments 8 pages, 6 figures, 3 tables

Explaining Reinforcement Learning Policies through Counterfactual Trajectories

Julius Frost, Olivia Watkins, Eric Weiner, Pieter Abbeel, Trevor Darrell, Bryan Plummer, Kate Saenko

Comments Accepted at ICML HILL 2021 Workshop

SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning

Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee

Comments Accepted to ICLR 2022

Hierarchical Few-Shot Imitation with Skill Transition Models

Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin

JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data

Kourosh Hakhamaneshi, Pieter Abbeel, Vladimir Stojanovic, Aditya Grover

Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents

Wenlong Huang, Pieter Abbeel, Deepak Pathak, Igor Mordatch

Comments Project website at https://huangwl18.github.io/language-planner

It Takes Four to Tango: Multiagent Selfplay for Automatic Curriculum Generation

Yuqing Du, Pieter Abbeel, Aditya Grover

ProMP: Proximal Meta-Policy Search

Jonas Rothfuss, Dennis Lee, Ignasi Clavera, Tamim Asfour, Pieter Abbeel

Comments The first three authors contributed equally. Published at ICLR 2019

Bingham Policy Parameterization for 3D Rotations in Reinforcement Learning

Stephen James, Pieter Abbeel

Comments Project page and code: https://sites.google.com/view/rl-bpp

Towards More Generalizable One-shot Visual Imitation Learning

Zhao Mandi, Fangchen Liu, Kimin Lee, Pieter Abbeel

Likelihood Contribution based Multi-scale Architecture for Generative Flows

Hari Prasanna Das, Pieter Abbeel, Costas J. Spanos

Contrastive Code Representation Learning

Paras Jain, Ajay Jain, Tianjun Zhang, Pieter Abbeel, Joseph E. Gonzalez, Ion Stoica

Comments In Proceedings of EMNLP 2021. 19 pages, 16 figures, 9 tables. Code available at https://github.com/parasj/contracode

Mastering Atari Games with Limited Data

Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao

Comments Published at NeurIPS 2021; Homepage: https://yewr.github.io/projects/efficientzero/

Target Entropy Annealing for Discrete Soft Actor-Critic

Yaosheng Xu, Dailin Hu, Litian Liang, Stephen McAleer, Pieter Abbeel, Roy Fox

Journal ref neurips 2021 deep rl workshop

Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL

Charles Packer, Pieter Abbeel, Joseph E. Gonzalez

Count-Based Temperature Scheduling for Maximum Entropy Reinforcement Learning

Dailin Hu, Pieter Abbeel, Roy Fox

Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning

Wenlong Huang, Igor Mordatch, Pieter Abbeel, Deepak Pathak

Comments Website at https://huangwl18.github.io/geometry-dex

B-Pref: Benchmarking Preference-Based Reinforcement Learning

Kimin Lee, Laura Smith, Anca Dragan, Pieter Abbeel

Comments NeurIPS Datasets and Benchmarks Track 2021. Code is available at https://github.com/rll-research/B-Pref

Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble

Seunghyun Lee, Younggyo Seo, Kimin Lee, Pieter Abbeel, Jinwoo Shin

Comments CoRL 2021. First two authors contributed equally

URLB: Unsupervised Reinforcement Learning Benchmark

Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel

Comments Code for the Unsupervised Reinforcement Learning Benchmark is available at https://github.com/rll-research/url_benchmark

Temporal-Difference Value Estimation via Uncertainty-Guided Soft Updates

Litian Liang, Yaosheng Xu, Stephen McAleer, Dailin Hu, Alexander Ihler, Pieter Abbeel, Roy Fox

Comments Accepted to Deep Reinforcement Learning Workshop @ NeurIPS 2021

Behavior From the Void: Unsupervised Active Pre-Training

Hao Liu, Pieter Abbeel

Comments Advances in Neural Information Processing Systems(NeurIPS), 2021 Spotlight