Abbeel, Pieter

281 publications

NeurIPS 2025 A Stable Whitening Optimizer for Efficient Neural Network Training Kevin Frans, Sergey Levine, Pieter Abbeel

ICLRW 2025 All-Atom Protein Generation with Latent Diffusion Amy X. Lu, Wilson Yan, Sarah A Robinson, Simon Kelow, Kevin K Yang, Vladimir Gligorijevic, Kyunghyun Cho, Richard Bonneau, Pieter Abbeel, Nathan C. Frey

NeurIPS 2025 Bigger, Regularized, Categorical: High-Capacity Value Functions Are Efficient Multi-Task Learners Michal Nauman, Marek Cygan, Carmelo Sferrazza, Aviral Kumar, Pieter Abbeel

ICML 2025 Chip Placement with Diffusion Models Vint Lee, Minh Nguyen, Leena Elzeiny, Chun Deng, Pieter Abbeel, John Wawrzynek

NeurIPS 2025 Coarse-to-Fine Q-Network with Action Sequence for Data-Efficient Reinforcement Learning Younggyo Seo, Pieter Abbeel

NeurIPS 2025 Compute-Optimal Scaling for Value-Based Deep RL Preston Fu, Oleh Rybkin, Zhiyuan Zhou, Michal Nauman, Pieter Abbeel, Sergey Levine, Aviral Kumar

NeurIPS 2025 DexGarmentLab: Dexterous Garment Manipulation Environment with Generalizable Policy Yuran Wang, Ruihai Wu, Yue Chen, Jiarui Wang, Jiaqi Liang, Ziyu Zhu, Haoran Geng, Jitendra Malik, Pieter Abbeel, Hao Dong

CVPR 2025 Efficient Long Video Tokenization via Coordinate-Based Patch Reconstruction Huiwon Jang, Sihyun Yu, Jinwoo Shin, Pieter Abbeel, Younggyo Seo

ICLR 2025 ElasticTok: Adaptive Tokenization for Image and Video Wilson Yan, Volodymyr Mnih, Aleksandra Faust, Matei Zaharia, Pieter Abbeel, Hao Liu

TMLR 2025 Interactive Task Planning with Language Models Boyi Li, Philipp Wu, Pieter Abbeel, Jitendra Malik

ICLR 2025 MaxInfoRL: Boosting Exploration in Reinforcement Learning Through Information Gain Maximization Bhavya Sukhija, Stelian Coros, Andreas Krause, Pieter Abbeel, Carmelo Sferrazza

ICML 2025 OTTER: A Vision-Language-Action Model with Text-Aware Visual Feature Extraction Huang Huang, Fangchen Liu, Letian Fu, Tingfan Wu, Mustafa Mukadam, Jitendra Malik, Ken Goldberg, Pieter Abbeel

NeurIPS 2025 Object-Centric 3D Motion Field for Robot Learning from Human Videos Zhao-Heng Yin, Sherry Yang, Pieter Abbeel

ICLR 2025 One Step Diffusion via Shortcut Models Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel

ICLRW 2025 Optimism via Intrinsic Rewards: Scalable and Principled Exploration for Model-Based Reinforcement Learning Bhavya Sukhija, Lenart Treven, Carmelo Sferrazza, Florian Dorfler, Pieter Abbeel, Andreas Krause

ICLR 2025 Prioritized Generative Replay Renhao Wang, Kevin Frans, Pieter Abbeel, Sergey Levine, Alexei A Efros

ICLR 2025 Protein Language Model Fitness Is a Matter of Preference Cade W Gordon, Amy X. Lu, Pieter Abbeel

ICLR 2025 SEMDICE: Off-Policy State Entropy Maximization via Stationary Distribution Correction Estimation Jongmin Lee, Meiqi Sun, Pieter Abbeel

NeurIPS 2025 SOMBRL: Scalable and Optimistic Model-Based RL Bhavya Sukhija, Lenart Treven, Carmelo Sferrazza, Florian Dorfler, Pieter Abbeel, Andreas Krause

CoRL 2025 The Sound of Simulation: Learning Multimodal Sim-to-Real Robot Policies with Generative Audio Renhao Wang, Haoran Geng, Tingle Li, Philipp Wu, Feishi Wang, Gopala Anumanchipalli, Trevor Darrell, Boyi Li, Pieter Abbeel, Jitendra Malik, Alexei A Efros

ICML 2025 Value-Based Deep RL Scales Predictably Oleh Rybkin, Michal Nauman, Preston Fu, Charlie Victor Snell, Pieter Abbeel, Sergey Levine, Aviral Kumar

ICLRW 2025 Value-Based Deep RL Scales Predictably Oleh Rybkin, Michal Nauman, Preston Fu, Charlie Victor Snell, Pieter Abbeel, Sergey Levine, Aviral Kumar

CoRL 2025 Visual Imitation Enables Contextual Humanoid Control Arthur Allshire, Hongsuk Choi, Junyi Zhang, David McAllister, Anthony Zhang, Chung Min Kim, Trevor Darrell, Pieter Abbeel, Jitendra Malik, Angjoo Kanazawa

ICLR 2025 World Model on Million-Length Video and Language with Blockwise RingAttention Hao Liu, Wilson Yan, Matei Zaharia, Pieter Abbeel

NeurIPS 2024 A StrongREJECT for Empty Jailbreaks Alexandra Souly, Qingyuan Lu, Dillon Bowen, Tu Trinh, Elvis Hsieh, Sana Pandey, Pieter Abbeel, Justin Svegliato, Scott Emmons, Olivia Watkins, Sam Toyer

ICLRW 2024 A StrongREJECT for Empty Jailbreaks Alexandra Souly, Qingyuan Lu, Dillon Bowen, Tu Trinh, Elvis Hsieh, Sana Pandey, Pieter Abbeel, Justin Svegliato, Scott Emmons, Olivia Watkins, Sam Toyer

CoRL 2024 Body Transformer: Leveraging Robot Embodiment for Policy Learning Carmelo Sferrazza, Dun-Ming Huang, Fangchen Liu, Jongmin Lee, Pieter Abbeel

ICLR 2024 Chain of Hindsight Aligns Language Models with Feedback Hao Liu, Carmelo Sferrazza, Pieter Abbeel

ICMLW 2024 Compressing the Latent Space of Single-Sequence Protein Predictors for Multimodal Generation Amy X. Lu, Wilson Yan, Vladimir Gligorijevic, Pieter Abbeel, Kevin K Yang, Nathan C. Frey

ICLR 2024 DreamSmooth: Improving Model-Based Reinforcement Learning via Reward Smoothing Vint Lee, Pieter Abbeel, Youngwoon Lee

AISTATS 2024 Functional Graphical Models: Structure Enables Offline Data-Driven Optimization Kuba Grudzien, Masatoshi Uehara, Sergey Levine, Pieter Abbeel

ICLR 2024 Learning Interactive Real-World Simulators Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Leslie Pack Kaelbling, Dale Schuurmans, Pieter Abbeel

CoRL 2024 Learning Robotic Locomotion Affordances and Photorealistic Simulators from Human-Captured Data Alejandro Escontrela, Justin Kerr, Kyle Stachowicz, Pieter Abbeel

ICML 2024 Learning a Diffusion Model Policy from Rewards via Q-Score Matching Michael Psenka, Alejandro Escontrela, Pieter Abbeel, Yi Ma

ICML 2024 Learning to Model the World with Language Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca Dragan

ICML 2024 Position: Video as the New Language for Real-World Decision Making Sherry Yang, Jacob C Walker, Jack Parker-Holder, Yilun Du, Jake Bruce, Andre Barreto, Pieter Abbeel, Dale Schuurmans

ICLR 2024 Probabilistic Adaptation of Black-Box Text-to-Video Models Sherry Yang, Yilun Du, Bo Dai, Dale Schuurmans, Joshua B. Tenenbaum, Pieter Abbeel

CoRL 2024 Reinforcement Learning with Foundation Priors: Let Embodied Agent Efficiently Learn on Its Own Weirui Ye, Yunsheng Zhang, Haoyang Weng, Xianfan Gu, Shengjie Wang, Tong Zhang, Mengchen Wang, Pieter Abbeel, Yang Gao

ICLR 2024 RingAttention with Blockwise Transformers for Near-Infinite Context Hao Liu, Matei Zaharia, Pieter Abbeel

ICLR 2024 Scalable Diffusion for Materials Generation Sherry Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk

ICLR 2024 Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell

ICLR 2024 The False Promise of Imitating Proprietary Language Models Arnav Gudibande, Eric Wallace, Charlie Victor Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song

CoRL 2024 Twisting Lids Off with Two Hands Toru Lin, Zhao-Heng Yin, Haozhi Qi, Pieter Abbeel, Jitendra Malik

ICML 2024 Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine

ICLR 2024 Video Language Planning Yilun Du, Sherry Yang, Pete Florence, Fei Xia, Ayzaan Wahid, Brian Ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Andy Zeng, Jonathan Tompson

NeurIPS 2024 Vision Foundation Model Enables Generalizable Object Pose Estimation Kai Chen, Yiyao Ma, Xingyu Lin, Stephen James, Jianshu Zhou, Yun-Hui Liu, Pieter Abbeel, Qi Dou

ICML 2024 Visual Representation Learning with Stochastic Frame Prediction Huiwon Jang, Dongyoung Kim, Junsu Kim, Jinwoo Shin, Pieter Abbeel, Younggyo Seo

NeurIPSW 2023 A Study on Improving Reasoning in Language Models Yuqing Du, Alexander Havrilla, Sainbayar Sukhbaatar, Pieter Abbeel, Roberta Raileanu

NeurIPS 2023 Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration Dongyoung Kim, Jinwoo Shin, Pieter Abbeel, Younggyo Seo

NeurIPS 2023 AlberDICE: Addressing Out-of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim

ICLR 2023 Become a Proficient Player with Limited Data Through Watching Pure Videos Weirui Ye, Yunsheng Zhang, Pieter Abbeel, Yang Gao

ICMLW 2023 Blockwise Parallel Transformer for Long Context Large Models Hao Liu, Pieter Abbeel

NeurIPS 2023 Blockwise Parallel Transformers for Large Context Models Hao Liu, Pieter Abbeel

ICML 2023 CLUTR: Curriculum Learning via Unsupervised Task Representation Learning Abdus Salam Azad, Izzeddin Gur, Jasper Emhoff, Nathaniel Alexis, Aleksandra Faust, Pieter Abbeel, Ion Stoica

ICML 2023 Controllability-Aware Unsupervised Skill Discovery Seohong Park, Kimin Lee, Youngwoon Lee, Pieter Abbeel

NeurIPS 2023 DPOK: Reinforcement Learning for Fine-Tuning Text-to-Image Diffusion Models Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee

ICLR 2023 Dichotomy of Control: Separating What You Can Control from What You Cannot Sherry Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

ICML 2023 Emergent Agentic Transformer from Chain of Hindsight Experience Hao Liu, Pieter Abbeel

NeurIPSW 2023 Exploration with Principles for Diverse AI Supervision Hao Liu, Matei Zaharia, Pieter Abbeel

NeurIPSW 2023 Exploration with Principles for Diverse AI Supervision Hao Liu, Matei Zaharia, Pieter Abbeel

NeurIPSW 2023 Exploration with Principles for Diverse AI Supervision Hao Liu, Matei Zaharia, Pieter Abbeel

ICML 2023 Guiding Pretraining in Reinforcement Learning with Large Language Models Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, Jacob Andreas

AAAI 2023 Improving Long-Horizon Imitation Through Instruction Prediction Joey Hejna, Pieter Abbeel, Lerrel Pinto

NeurIPS 2023 Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment Hao Liu, Wilson Yan, Pieter Abbeel

CoRL 2023 Language-Conditioned Path Planning Amber Xie, Youngwoon Lee, Pieter Abbeel, Stephen James

NeurIPSW 2023 Learning Interactive Real-World Simulators Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Dale Schuurmans, Pieter Abbeel

NeurIPSW 2023 Learning Interactive Real-World Simulators Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Dale Schuurmans, Pieter Abbeel

NeurIPS 2023 Learning Universal Policies via Text-Guided Video Generation Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel

ICML 2023 Masked Trajectory Models for Prediction, Representation, and Control Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran

ICLRW 2023 Masked Trajectory Models for Prediction, Representation, and Control Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran

ICML 2023 Multi-Environment Pretraining Enables Transfer to Action Limited Datasets David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum

ICLRW 2023 Multi-Environment Pretraining Enables Transfer to Action Limited Datasets David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum

ICML 2023 Multi-View Masked World Models for Visual Robotic Manipulation Younggyo Seo, Junsu Kim, Stephen James, Kimin Lee, Jinwoo Shin, Pieter Abbeel

ICLR 2023 Preference Transformer: Modeling Human Preferences Using Transformers for RL Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee

NeurIPSW 2023 Ring Attention with Blockwise Transformers for Near-Infinite Context Hao Liu, Matei Zaharia, Pieter Abbeel

NeurIPSW 2023 Ring Attention with Blockwise Transformers for Near-Infinite Context Hao Liu, Matei Zaharia, Pieter Abbeel

CoRL 2023 RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning Kevin Zakka, Philipp Wu, Laura Smith, Nimrod Gileadi, Taylor Howell, Xue Bin Peng, Sumeet Singh, Yuval Tassa, Pete Florence, Andy Zeng, Pieter Abbeel

NeurIPSW 2023 Scalable Diffusion for Materials Generation Sherry Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk

NeurIPSW 2023 Scalable Diffusion for Materials Generation Sherry Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk

NeurIPSW 2023 Skill-Based Reinforcement Learning with Intrinsic Reward Matching Ademi Adeniji, Amber Xie, Pieter Abbeel

ICML 2023 Temporally Consistent Transformers for Video Generation Wilson Yan, Danijar Hafner, Stephen James, Pieter Abbeel

NeurIPSW 2023 Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game Sam Toyer, Olivia Watkins, Ethan Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell

NeurIPSW 2023 Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell

ICML 2023 The Wisdom of Hindsight Makes Language Models Better Instruction Followers Tianjun Zhang, Fangchen Liu, Justin Wong, Pieter Abbeel, Joseph E. Gonzalez

CVPR 2023 VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models Ajay Jain, Amber Xie, Pieter Abbeel

NeurIPS 2023 Video Prediction Models as Rewards for Reinforcement Learning Alejandro Escontrela, Ademi Adeniji, Wilson Yan, Ajay N. Jain, Xue Bin Peng, Ken Goldberg, Youngwoon Lee, Danijar Hafner, Pieter Abbeel

NeurIPSW 2023 What Can AI Learn from Human Exploration? Intrinsically-Motivated Humans and Agents in Open-World Exploration Yuqing Du, Eliza Kosoy, Alyssa Li Dayan, Maria Rufova, Alison Gopnik, Pieter Abbeel

NeurIPSW 2023 What Can AI Learn from Human Exploration? Intrinsically-Motivated Humans and Agents in Open-World Exploration Yuqing Du, Eliza Kosoy, Alyssa Dayan, Maria Rufova, Pieter Abbeel, Alison Gopnik

NeurIPSW 2023 What Can AI Learn from Human Exploration? Intrinsically-Motivated Humans and Agents in Open-World Exploration Yuqing Du, Eliza Kosoy, Alyssa Dayan, Maria Rufova, Pieter Abbeel, Alison Gopnik

NeurIPS 2023 Where Are We in the Search for an Artificial Visual Cortex for Embodied Intelligence? Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Tingfan Wu, Jay Vakil, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

ICLRW 2023 Where Are We in the Search for an Artificial Visual Cortex for Embodied Intelligence? Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Pieter Abbeel, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

UAI 2022 AdaCat: Adaptive Categorical Discretization for Autoregressive Models Qiyang Li, Ajay Jain, Pieter Abbeel

ECCV 2022 Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction YuXuan Liu, Nikhil Mishra, Maximilian Sieb, Yide Shentu, Pieter Abbeel, Xi Chen

NeurIPSW 2022 CLUTR: Curriculum Learning via Unsupervised Task Representation Learning Abdus Salam Azad, Izzeddin Gur, Aleksandra Faust, Pieter Abbeel, Ion Stoica

NeurIPSW 2022 CLUTR: Curriculum Learning via Unsupervised Task Representation Learning Abdus Salam Azad, Izzeddin Gur, Aleksandra Faust, Pieter Abbeel, Ion Stoica

NeurIPS 2022 Chain of Thought Imitation with Procedure Cloning Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

CoRL 2022 DayDreamer: World Models for Physical Robot Learning Philipp Wu, Alejandro Escontrela, Danijar Hafner, Pieter Abbeel, Ken Goldberg

NeurIPS 2022 Deep Hierarchical Planning from Pixels Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel

ICLRW 2022 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

CoRL 2022 Fleet-DAgger: Interactive Robot Fleet Learning with Scalable Human Supervision Ryan Hoque, Lawrence Yunliang Chen, Satvik Sharma, Karthik Dharmarajan, Brijen Thananjeyan, Pieter Abbeel, Ken Goldberg

AAAI 2022 Frozen Pretrained Transformers as Universal Computation Engines Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch

ICLR 2022 Hierarchical Few-Shot Imitation with Skill Transition Models Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin

ICLR 2022 It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation Yuqing Du, Pieter Abbeel, Aditya Grover

ICML 2022 Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents Wenlong Huang, Pieter Abbeel, Deepak Pathak, Igor Mordatch

NeurIPS 2022 Masked Autoencoding for Scalable and Generalizable Decision Making Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel

CoRL 2022 Masked World Models for Visual Control Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel

NeurIPSW 2022 Multi-Environment Pretraining Enables Transfer to Action Limited Datasets David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum

ICMLW 2022 Multimodal Masked Autoencoders Learn Transferable Representations Xinyang Geng, Hao Liu, Lisa Lee, Dale Schuurmans, Sergey Levine, Pieter Abbeel

NeurIPS 2022 On the Effectiveness of Fine-Tuning Versus Meta-Reinforcement Learning Mandi Zhao, Pieter Abbeel, Stephen James

AAAI 2022 Programmatic Modeling and Generation of Real-Time Strategic Soccer Environments for Reinforcement Learning Abdus Salam Azad, Edward Kim, Qiancheng Wu, Kimin Lee, Ion Stoica, Pieter Abbeel, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia

NeurIPSW 2022 Quantifying Uncertainty in Foundation Models via Ensembles Meiqi Sun, Wilson Yan, Pieter Abbeel, Igor Mordatch

CoRL 2022 Real-World Robot Learning with Masked Visual Pre-Training Ilija Radosavovic, Tete Xiao, Stephen James, Pieter Abbeel, Jitendra Malik, Trevor Darrell

ICML 2022 Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks Litian Liang, Yaosheng Xu, Stephen Mcaleer, Dailin Hu, Alexander Ihler, Pieter Abbeel, Roy Fox

ICML 2022 Reinforcement Learning with Action-Free Pre-Training from Videos Younggyo Seo, Kimin Lee, Stephen L James, Pieter Abbeel

ICLR 2022 Reward Uncertainty for Exploration in Preference-Based Reinforcement Learning Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel

ICLR 2022 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

ECCV 2022 Sim-to-Real 6d Object Pose Estimation via Iterative Self-Training for Robotic Bin Picking Kai Chen, Rui Cao, Stephen James, Yichuan Li, Yun-Hui Liu, Pieter Abbeel, Qi Dou

CoRL 2022 Sim-to-Real via Sim-to-Seg: End-to-End Off-Road Autonomous Driving Without Real Data John So, Amber Xie, Sunggoo Jung, Jeffrey Edlund, Rohan Thakker, Ali-akbar Agha-mohammadi, Pieter Abbeel, Stephen James

NeurIPS 2022 Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions Weirui Ye, Pieter Abbeel, Yang Gao

NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta

NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta

NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta

NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta

NeurIPS 2022 Unsupervised Reinforcement Learning with Contrastive Intrinsic Control Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel

CVPR 2022 Zero-Shot Text-Guided Object Generation with Dream Fields Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole

NeurIPSW 2021 A Framework for Efficient Robotic Manipulation Albert Zhan, Ruihan Zhao, Lerrel Pinto, Pieter Abbeel, Michael Laskin

ICML 2021 APS: Active Pretraining with Successor Features Hao Liu, Pieter Abbeel

NeurIPS 2021 Behavior from the Void: Unsupervised Active Pre-Training Hao Liu, Pieter Abbeel

NeurIPSW 2021 Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL Catherine Cang, Aravind Rajeswaran, Pieter Abbeel, Michael Laskin

CVPR 2021 Bottleneck Transformers for Visual Recognition Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani

NeurIPSW 2021 CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel

NeurIPSW 2021 Count-Based Temperature Scheduling for Maximum Entropy Reinforcement Learning Dailin Hu, Pieter Abbeel, Roy Fox

ICMLW 2021 Data-Efficient Exploration with Self Play for Atari Michael Laskin, Catherine Cang, Ryan Rudes, Pieter Abbeel

NeurIPS 2021 Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch

ICMLW 2021 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

ICML 2021 Decoupling Representation Learning from Reinforcement Learning Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin

ICLR 2021 Efficient Empowerment Estimation for Unsupervised Stabilization Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin

ICMLW 2021 Hierarchical Few-Shot Imitation with Skill Transition Models Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin

NeurIPSW 2021 Hierarchical Few-Shot Imitation with Skill Transition Models Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin

NeurIPS 2021 Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL Charles Packer, Pieter Abbeel, Joseph E Gonzalez

NeurIPS 2021 Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel

ICLR 2021 Learning What to Do by Simulating the past David Lindner, Rohin Shah, Pieter Abbeel, Anca Dragan

ICML 2021 MSA Transformer Roshan M Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives

NeurIPS 2021 Mastering Atari Games with Limited Data Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao

ICLR 2021 Mutual Information State Intrinsic Control Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu

CoRL 2021 Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble Seunghyun Lee, Younggyo Seo, Kimin Lee, Pieter Abbeel, Jinwoo Shin

ICML 2021 PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-Training Kimin Lee, Laura M Smith, Pieter Abbeel

ICCV 2021 Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Ajay Jain, Matthew Tancik, Pieter Abbeel

NeurIPS 2021 Reinforcement Learning with Latent Flow Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Misha Laskin

ICLR 2021 Reset-Free Lifelong Learning with Skill-Space Planning Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch

NeurIPSW 2021 Reward Uncertainty for Exploration in Preference-Based Reinforcement Learning Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel

ICML 2021 SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel

NeurIPSW 2021 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

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

CoRL 2021 Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin

NeurIPSW 2021 Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin

ICML 2021 State Entropy Maximization with Random Encoders for Efficient Exploration Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee

NeurIPSW 2021 Target Entropy Annealing for Discrete Soft Actor-Critic Yaosheng Xu, Dailin Hu, Litian Liang, Stephen Marcus McAleer, Pieter Abbeel, Roy Fox

ICLR 2021 Task-Agnostic Morphology Evolution Donald Joseph Hejna Iii, Pieter Abbeel, Lerrel Pinto

NeurIPS 2021 Teachable Reinforcement Learning via Advice Distillation Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas

NeurIPSW 2021 Temporal-Difference Value Estimation via Uncertainty-Guided Soft Updates Litian Liang, Yaosheng Xu, Stephen Marcus McAleer, Dailin Hu, Alexander Ihler, Pieter Abbeel, Roy Fox

NeurIPSW 2021 URLB: Unsupervised Reinforcement Learning Benchmark Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel

ICML 2021 Unsupervised Learning of Visual 3D Keypoints for Control Boyuan Chen, Pieter Abbeel, Deepak Pathak

NeurIPS 2020 Automatic Curriculum Learning Through Value Disagreement Yunzhi Zhang, Pieter Abbeel, Lerrel Pinto

NeurIPS 2020 AvE: Assistance via Empowerment Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca Dragan

ICML 2020 CURL: Contrastive Unsupervised Representations for Reinforcement Learning Michael Laskin, Aravind Srinivas, Pieter Abbeel

NeurIPS 2020 Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay N. Jain, Pieter Abbeel

NeurIPS 2020 Generalized Hindsight for Reinforcement Learning Alexander Li, Lerrel Pinto, Pieter Abbeel

ICML 2020 Hallucinative Topological Memory for Zero-Shot Visual Planning Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar

ICML 2020 Hierarchically Decoupled Imitation for Morphological Transfer Donald Hejna, Lerrel Pinto, Pieter Abbeel

CoRL 2020 Learning Predictive Representations for Deformable Objects Using Contrastive Estimation Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto

UAI 2020 Locally Masked Convolution for Autoregressive Models Ajay Jain, Pieter Abbeel, Deepak Pathak

ICLR 2020 Model-Augmented Actor-Critic: Backpropagating Through Paths Ignasi Clavera, Violet Fu, Pieter Abbeel

L4DC 2020 Plan2Vec: Unsupervised Representation Learning by Latent Plans Ge Yang, Amy Zhang, Ari Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra

ICML 2020 Planning to Explore via Self-Supervised World Models Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak

NeurIPS 2020 Reinforcement Learning with Augmented Data Misha Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas

ICML 2020 Responsive Safety in Reinforcement Learning by PID Lagrangian Methods Adam Stooke, Joshua Achiam, Pieter Abbeel

NeurIPS 2020 Sparse Graphical Memory for Robust Planning Scott Emmons, Ajay N. Jain, Misha Laskin, Thanard Kurutach, Pieter Abbeel, Deepak Pathak

NeurIPS 2020 Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model Alex X. Lee, Anusha Nagabandi, Pieter Abbeel, Sergey Levine

ICLR 2020 Sub-Policy Adaptation for Hierarchical Reinforcement Learning Alexander C. Li, Carlos Florensa, Ignasi Clavera, Pieter Abbeel

NeurIPS 2020 Trajectory-Wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning Younggyo Seo, Kimin Lee, Ignasi Clavera Gilaberte, Thanard Kurutach, Jinwoo Shin, Pieter Abbeel

ICML 2020 Variable Skipping for Autoregressive Range Density Estimation Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Peter Chen

CoRL 2020 Visual Imitation Made Easy Sarah Young, Dhiraj Gandhi, Shubham Tulsiani, Abhinav Gupta, Pieter Abbeel, Lerrel Pinto

NeurIPS 2019 Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs Himanshu Sahni, Toby Buckley, Pieter Abbeel, Ilya Kuzovkin

ICMLW 2019 Addressing Sample Complexity in Visual Tasks Using Hindsight Experience Replay and Hallucinatory GANs Himanshu Sahni, Toby Buckley, Pieter Abbeel, Ilya Kuzovkin

CoRL 2019 Asynchronous Methods for Model-Based Reinforcement Learning Yunzhi Zhang, Ignasi Clavera, Boren Tsai, Pieter Abbeel

ICML 2019 Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables Friso Kingma, Pieter Abbeel, Jonathan Ho

NeurIPS 2019 Compositional Plan Vectors Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine

NeurIPS 2019 Compression with Flows via Local Bits-Back Coding Jonathan Ho, Evan Lohn, Pieter Abbeel

NeurIPS 2019 Evaluating Protein Transfer Learning with TAPE Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Peter Chen, John Canny, Pieter Abbeel, Yun Song

ICML 2019 Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel

NeurIPS 2019 Geometry-Aware Neural Rendering Joshua Tobin, Wojciech Zaremba, Pieter Abbeel

NeurIPS 2019 Goal-Conditioned Imitation Learning Yiming Ding, Carlos Florensa, Pieter Abbeel, Mariano Phielipp

ICMLW 2019 Goal-Conditioned Imitation Learning Yiming Ding, Carlos Florensa, Mariano Phielipp, Pieter Abbeel

NeurIPS 2019 Guided Meta-Policy Search Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn

ICLR 2019 Guiding Policies with Language via Meta-Learning John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas, John DeNero, Pieter Abbeel, Sergey Levine

ICLR 2019 Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning Anusha Nagabandi, Ignasi Clavera, Simin Liu, Ronald S. Fearing, Pieter Abbeel, Sergey Levine, Chelsea Finn

NeurIPS 2019 MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine

ICML 2019 On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Rohin Shah, Noah Gundotra, Pieter Abbeel, Anca Dragan

NeurIPS 2019 On the Utility of Learning About Humans for Human-AI Coordination Micah Carroll, Rohin Shah, Mark K Ho, Tom Griffiths, Sanjit Seshia, Pieter Abbeel, Anca Dragan

ICML 2019 Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules Daniel Ho, Eric Liang, Xi Chen, Ion Stoica, Pieter Abbeel

ICLR 2019 Preferences Implicit in the State of the World Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca Dragan

ICLR 2019 ProMP: Proximal Meta-Policy Search Jonas Rothfuss, Dennis Lee, Ignasi Clavera, Tamim Asfour, Pieter Abbeel

ICML 2019 SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew Johnson, Sergey Levine

ICMLW 2019 Sub-Policy Adaptation for Hierarchical Reinforcement Learning Alexander Li, Carlos Florensa, Pieter Abbeel

ICLR 2019 Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine

ICLR 2018 A Simple Neural Attentive Meta-Learner Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, Pieter Abbeel

ICML 2018 Automatic Goal Generation for Reinforcement Learning Agents Carlos Florensa, David Held, Xinyang Geng, Pieter Abbeel

CoRL 2018 Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation Gregory Kahn, Adam Villaflor, Pieter Abbeel, Sergey Levine

ICLR 2018 Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments Maruan Al-Shedivat, Trapit Bansal, Yura Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel

AAAI 2018 Emergence of Grounded Compositional Language in Multi-Agent Populations Igor Mordatch, Pieter Abbeel

NeurIPS 2018 Evolved Policy Gradients Rein Houthooft, Yuhua Chen, Phillip Isola, Bradly Stadie, Filip Wolski, OpenAI Jonathan Ho, Pieter Abbeel

ICML 2018 Latent Space Policies for Hierarchical Reinforcement Learning Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, Sergey Levine

NeurIPS 2018 Learning Plannable Representations with Causal InfoGAN Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell, Pieter Abbeel

ICLR 2018 Meta Learning Shared Hierarchies Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, John Schulman

NeurIPS 2018 Meta-Reinforcement Learning of Structured Exploration Strategies Abhishek Gupta, Russell Mendonca, YuXuan Liu, Pieter Abbeel, Sergey Levine

CoRL 2018 Model-Based Reinforcement Learning via Meta-Policy Optimization Ignasi Clavera, Jonas Rothfuss, John Schulman, Yasuhiro Fujita, Tamim Asfour, Pieter Abbeel

ICLR 2018 Model-Ensemble Trust-Region Policy Optimization Thanard Kurutach, Ignasi Clavera, Yan Duan, Aviv Tamar, Pieter Abbeel

ICLR 2018 Parameter Space Noise for Exploration Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y. Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, Marcin Andrychowicz

ICML 2018 PixelSNAIL: An Improved Autoregressive Generative Model Xi Chen, Nikhil Mishra, Mostafa Rohaninejad, Pieter Abbeel

ICML 2018 Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings John Co-Reyes, YuXuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine

ICML 2018 Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine

NeurIPS 2018 The Importance of Sampling inMeta-Reinforcement Learning Bradly Stadie, Ge Yang, Rein Houthooft, Peter Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

ICML 2018 Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn

ICLR 2018 Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M Bayen, Sham Kakade, Igor Mordatch, Pieter Abbeel

NeurIPS 2017 #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, OpenAI Xi Chen, Yan Duan, John Schulman, Filip DeTurck, Pieter Abbeel

ICLR 2017 Adversarial Attacks on Neural Network Policies Sandy H. Huang, Nicolas Papernot, Ian J. Goodfellow, Yan Duan, Pieter Abbeel

ICML 2017 Constrained Policy Optimization Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel

ICLR 2017 Generalizing Skills with Semi-Supervised Reinforcement Learning Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine

UAI 2017 Inverse Reinforcement Learning via Deep Gaussian Process Ming Jin, Andreas C. Damianou, Pieter Abbeel, Costas J. Spanos

NeurIPS 2017 Inverse Reward Design Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart Russell, Anca Dragan

ICLR 2017 Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine

ICLR 2017 Learning Visual Servoing with Deep Features and Fitted Q-Iteration Alex X. Lee, Sergey Levine, Pieter Abbeel

ICML 2017 Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn, Pieter Abbeel, Sergey Levine

CoRL 2017 Mutual Alignment Transfer Learning Markus Wulfmeier, Ingmar Posner, Pieter Abbeel

NeurIPS 2017 One-Shot Imitation Learning Yan Duan, Marcin Andrychowicz, Bradly Stadie, OpenAI Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba

CoRL 2017 One-Shot Visual Imitation Learning via Meta-Learning Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine

ICML 2017 Prediction and Control with Temporal Segment Models Nikhil Mishra, Pieter Abbeel, Igor Mordatch

ICML 2017 Reinforcement Learning with Deep Energy-Based Policies Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, Sergey Levine

CoRL 2017 Reverse Curriculum Generation for Reinforcement Learning Carlos Florensa, David Held, Markus Wulfmeier, Michael Zhang, Pieter Abbeel

ICLR 2017 Stochastic Neural Networks for Hierarchical Reinforcement Learning Carlos Florensa, Yan Duan, Pieter Abbeel

IJCAI 2017 The Off-Switch Game Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell

ICLR 2017 Third Person Imitation Learning Bradly C. Stadie, Pieter Abbeel, Ilya Sutskever

IJCAI 2017 Value Iteration Networks Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel

ICLR 2017 Variational Lossy Autoencoder Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel

NeurIPS 2016 Backprop KF: Learning Discriminative Deterministic State Estimators Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel

ICML 2016 Benchmarking Deep Reinforcement Learning for Continuous Control Yan Duan, Xi Chen, Rein Houthooft, John Schulman, Pieter Abbeel

NeurIPS 2016 Combinatorial Energy Learning for Image Segmentation Jeremy B Maitin-Shepard, Viren Jain, Michal Januszewski, Peter Li, Pieter Abbeel

NeurIPS 2016 Cooperative Inverse Reinforcement Learning Dylan Hadfield-Menell, Stuart Russell, Pieter Abbeel, Anca Dragan

JMLR 2016 End-to-End Training of Deep Visuomotor Policies Sergey Levine, Chelsea Finn, Trevor Darrell, Pieter Abbeel

ICML 2016 Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization Chelsea Finn, Sergey Levine, Pieter Abbeel

ICLR 2016 High-Dimensional Continuous Control Using Generalized Advantage Estimation John Schulman, Philipp Moritz, Sergey Levine, Michael I. Jordan, Pieter Abbeel

NeurIPS 2016 InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel

NeurIPS 2016 Learning to Poke by Poking: Experiential Learning of Intuitive Physics Pulkit Agrawal, Ashvin V Nair, Pieter Abbeel, Jitendra Malik, Sergey Levine

NeurIPS 2016 VIME: Variational Information Maximizing Exploration Rein Houthooft, Xi Chen, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel

NeurIPS 2016 Value Iteration Networks Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel

ICML 2015 Alpha-Beta Divergences Discover Micro and Macro Structures in Data Karthik Narayan, Ali Punjani, Pieter Abbeel

NeurIPS 2015 Gradient Estimation Using Stochastic Computation Graphs John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

AAAI 2015 Tractability of Planning with Loops Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell

ICML 2015 Trust Region Policy Optimization John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, Philipp Moritz

NeurIPS 2014 Learning Neural Network Policies with Guided Policy Search Under Unknown Dynamics Sergey Levine, Pieter Abbeel

ECCV 2014 Optimization-Based Artifact Correction for Electron Microscopy Image Stacks Samaneh Azadi, Jeremy Maitin-Shepard, Pieter Abbeel

ECML-PKDD 2012 Machine Learning for Robotics Pieter Abbeel

NeurIPS 2012 Risk Aversion in Markov Decision Processes via near Optimal Chernoff Bounds Teodor M. Moldovan, Pieter Abbeel

ICML 2012 Safe Exploration in Markov Decision Processes Teodor Mihai Moldovan, Pieter Abbeel

NeurIPS 2010 On a Connection Between Importance Sampling and the Likelihood Ratio Policy Gradient Tang Jie, Pieter Abbeel

ICML 2008 Learning for Control from Multiple Demonstrations Adam Coates, Pieter Abbeel, Andrew Y. Ng

JMLR 2008 Max-Margin Classification of Data with Absent Features Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

NeurIPS 2007 Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion J. Z. Kolter, Pieter Abbeel, Andrew Y. Ng

NeurIPS 2006 An Application of Reinforcement Learning to Aerobatic Helicopter Flight Pieter Abbeel, Adam Coates, Morgan Quigley, Andrew Y. Ng

AAAI 2006 Efficient L1 Regularized Logistic Regression Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. Ng

JMLR 2006 Learning Factor Graphs in Polynomial Time and Sample Complexity Pieter Abbeel, Daphne Koller, Andrew Y. Ng

NeurIPS 2006 Max-Margin Classification of Incomplete Data Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

ICML 2006 Using Inaccurate Models in Reinforcement Learning Pieter Abbeel, Morgan Quigley, Andrew Y. Ng

ICML 2005 Exploration and Apprenticeship Learning in Reinforcement Learning Pieter Abbeel, Andrew Y. Ng

UAI 2005 Learning Factor Graphs in Polynomial Time & Sample Complexity Pieter Abbeel, Daphne Koller, Andrew Y. Ng

NeurIPS 2005 Learning Vehicular Dynamics, with Application to Modeling Helicopters Pieter Abbeel, Varun Ganapathi, Andrew Y. Ng

ICML 2004 Apprenticeship Learning via Inverse Reinforcement Learning Pieter Abbeel, Andrew Y. Ng

NeurIPS 2004 Learning First-Order Markov Models for Control Pieter Abbeel, Andrew Y. Ng

NeurIPS 2003 Link Prediction in Relational Data Ben Taskar, Ming-fai Wong, Pieter Abbeel, Daphne Koller

UAI 2002 Discriminative Probabilistic Models for Relational Data Benjamin Taskar, Pieter Abbeel, Daphne Koller