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ORCIDPieter Abbeel
Person information
- affiliation: University of California, Berkeley, USA
- affiliation: Stanford University, USA
- award (2021): ACM Prize in Computing
- award (2013): Presidential Early Career Award for Scientists and Engineers
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2020 – today
- 2023
[i285]Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel:
Learning Universal Policies via Text-Guided Video Generation. CoRR abs/2302.00111 (2023)- [i284]Hao Liu, Wilson Yan, Pieter Abbeel:
Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment. CoRR abs/2302.00902 (2023) - [i283]Younggyo Seo, Junsu Kim, Stephen James, Kimin Lee, Jinwoo Shin, Pieter Abbeel:
Multi-View Masked World Models for Visual Robotic Manipulation. CoRR abs/2302.02408 (2023) - [i282]Hao Liu, Carmelo Sferrazza, Pieter Abbeel:
Chain of Hindsight Aligns Language Models with Feedback. CoRR abs/2302.02676 (2023) - [i281]Seohong Park, Kimin Lee, Youngwoon Lee, Pieter Abbeel:
Controllability-Aware Unsupervised Skill Discovery. CoRR abs/2302.05103 (2023) - [i280]Tianjun Zhang, Fangchen Liu, Justin Wong, Pieter Abbeel, Joseph E. Gonzalez:
The Wisdom of Hindsight Makes Language Models Better Instruction Followers. CoRR abs/2302.05206 (2023) - [i279]Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, Jacob Andreas:
Guiding Pretraining in Reinforcement Learning with Large Language Models. CoRR abs/2302.06692 (2023) - [i278]Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath:
Robust and Versatile Bipedal Jumping Control through Multi-Task Reinforcement Learning. CoRR abs/2302.09450 (2023) - [i277]Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Shixiang Shane Gu:
Aligning Text-to-Image Models using Human Feedback. CoRR abs/2302.12192 (2023) - [i276]Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
Preference Transformer: Modeling Human Preferences using Transformers for RL. CoRR abs/2303.00957 (2023) - [i275]Sherry Yang, Ofir Nachum, Yilun Du, Jason Wei, Pieter Abbeel, Dale Schuurmans:
Foundation Models for Decision Making: Problems, Methods, and Opportunities. CoRR abs/2303.04129 (2023) - [i274]Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier:
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? CoRR abs/2303.18240 (2023) - [i273]Kevin Zakka, Laura M. Smith, Nimrod Gileadi, Taylor A. Howell, Xue Bin Peng, Sumeet Singh, Yuval Tassa, Pete Florence, Andy Zeng, Pieter Abbeel:
RoboPianist: A Benchmark for High-Dimensional Robot Control. CoRR abs/2304.04150 (2023) - [i272]Yuxuan Liu, Nikhil Mishra, Pieter Abbeel, Xi Chen:
Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN. CoRR abs/2305.01910 (2023) - [i271]Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran:
Masked Trajectory Models for Prediction, Representation, and Control. CoRR abs/2305.02968 (2023) - [i270]Yuxuan Liu, Xi Chen, Pieter Abbeel:
Self-Supervised Instance Segmentation by Grasping. CoRR abs/2305.06305 (2023) - 2022
- [j26]Freek Stulp
, Michael Spranger, Kim Listmann, Stéphane Doncieux, Moritz Tenorth, George Konidaris, Pieter Abbeel:
Innovation Paths for Machine Learning in Robotics [Industry Activities]. IEEE Robotics Autom. Mag. 29(4): 141-144 (2022) - [c291]Abdus Salam Azad, Edward Kim, Qiancheng Wu, Kimin Lee, Ion Stoica, Pieter Abbeel, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia:
Programmatic Modeling and Generation of Real-Time Strategic Soccer Environments for Reinforcement Learning. AAAI 2022: 6028-6036 - [c290]Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch:
Frozen Pretrained Transformers as Universal Computation Engines. AAAI 2022: 7628-7636 - [c289]Ryan Hoque, Lawrence Yunliang Chen, Satvik Sharma, Karthik Dharmarajan, Brijen Thananjeyan, Pieter Abbeel, Ken Goldberg:
Fleet-DAgger: Interactive Robot Fleet Learning with Scalable Human Supervision. CoRL 2022: 368-380 - [c288]Ilija Radosavovic, Tete Xiao, Stephen James, Pieter Abbeel, Jitendra Malik, Trevor Darrell:
Real-World Robot Learning with Masked Visual Pre-training. CoRL 2022: 416-426 - [c287]Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel:
Masked World Models for Visual Control. CoRL 2022: 1332-1344 - [c286]John So, Amber Xie, Sunggoo Jung, Jeffrey A. Edlund, Rohan Thakker, Ali-akbar Agha-mohammadi, Pieter Abbeel, Stephen James:
Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real Data. CoRL 2022: 1871-1881 - [c285]Philipp Wu, Alejandro Escontrela, Danijar Hafner, Pieter Abbeel, Ken Goldberg:
DayDreamer: World Models for Physical Robot Learning. CoRL 2022: 2226-2240 - [c284]Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole:
Zero-Shot Text-Guided Object Generation with Dream Fields. CVPR 2022: 857-866 - [c283]Kai Chen, Rui Cao, Stephen James, Yichuan Li, Yun-Hui Liu, Pieter Abbeel, Qi Dou:
Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking. ECCV (39) 2022: 533-550 - [c282]Yuxuan Liu, Nikhil Mishra, Maximilian Sieb, Yide Shentu, Pieter Abbeel, Xi Chen:
Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction. ECCV (10) 2022: 673-694 - [c281]Younggyo Seo, Kimin Lee, Fangchen Liu, Stephen James, Pieter Abbeel:
HARP: Autoregressive Latent Video Prediction with High-Fidelity Image Generator. ICIP 2022: 3943-3947 - [c280]Yuqing Du, Pieter Abbeel, Aditya Grover:
It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation. ICLR 2022 - [c279]Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin:
Hierarchical Few-Shot Imitation with Skill Transition Models. ICLR 2022 - [c278]Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel:
Reward Uncertainty for Exploration in Preference-based Reinforcement Learning. ICLR 2022 - [c277]Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. ICLR 2022 - [c276]Wenlong Huang, Pieter Abbeel, Deepak Pathak, Igor Mordatch:
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents. ICML 2022: 9118-9147 - [c275]Litian Liang, Yaosheng Xu, Stephen McAleer, Dailin Hu, Alexander Ihler, Pieter Abbeel, Roy Fox:
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks. ICML 2022: 13285-13301 - [c274]Younggyo Seo, Kimin Lee, Stephen L. James, Pieter Abbeel:
Reinforcement Learning with Action-Free Pre-Training from Videos. ICML 2022: 19561-19579 - [c273]Mandi Zhao, Fangchen Liu, Kimin Lee, Pieter Abbeel:
Towards More Generalizable One-shot Visual Imitation Learning. ICRA 2022: 2434-2444 - [c272]Alejandro Escontrela, Xue Bin Peng, Wenhao Yu, Tingnan Zhang, Atil Iscen, Ken Goldberg, Pieter Abbeel:
Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions. IROS 2022: 25-32 - [c271]Sarah Young, Jyothish Pari, Pieter Abbeel, Lerrel Pinto:
Playful Interactions for Representation Learning. IROS 2022: 992-999 - [c270]Albert Zhan, Ruihan Zhao, Lerrel Pinto, Pieter Abbeel, Michael Laskin:
Learning Visual Robotic Control Efficiently with Contrastive Pre-training and Data Augmentation. IROS 2022: 4040-4047 - [c269]Kyle Hollins Wray, Stas Tiomkin, Mykel J. Kochenderfer, Pieter Abbeel:
Multi-Objective Policy Gradients with Topological Constraints. IROS 2022: 9034-9039 - [c268]Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel:
Deep Hierarchical Planning from Pixels. NeurIPS 2022 - [c267]Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel:
Unsupervised Reinforcement Learning with Contrastive Intrinsic Control. NeurIPS 2022 - [c266]Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel:
Masked Autoencoding for Scalable and Generalizable Decision Making. NeurIPS 2022 - [c265]Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum:
Chain of Thought Imitation with Procedure Cloning. NeurIPS 2022 - [c264]Weirui Ye, Pieter Abbeel, Yang Gao:
Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions. NeurIPS 2022 - [c263]Mandi Zhao, Pieter Abbeel, Stephen James:
On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning. NeurIPS 2022 - [c262]Qiyang Li, Ajay Jain, Pieter Abbeel:
AdaCat: Adaptive categorical discretization for autoregressive models. UAI 2022: 1188-1198 - [i269]Wenlong Huang, Pieter Abbeel, Deepak Pathak, Igor Mordatch:
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents. CoRR abs/2201.07207 (2022) - [i268]Julius Frost, Olivia Watkins, Eric Weiner, Pieter Abbeel, Trevor Darrell, Bryan A. Plummer, Kate Saenko:
Explaining Reinforcement Learning Policies through Counterfactual Trajectories. CoRR abs/2201.12462 (2022) - [i267]Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto:
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning. CoRR abs/2201.13425 (2022) - [i266]Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel:
CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery. CoRR abs/2202.00161 (2022) - [i265]Stephen James, Pieter Abbeel:
Bingham Policy Parameterization for 3D Rotations in Reinforcement Learning. CoRR abs/2202.03957 (2022) - [i264]Yuqing Du, Pieter Abbeel, Aditya Grover:
It Takes Four to Tango: Multiagent Selfplay for Automatic Curriculum Generation. CoRR abs/2202.10608 (2022) - [i263]Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. CoRR abs/2203.10050 (2022) - [i262]Olivia Watkins, Trevor Darrell, Pieter Abbeel, Jacob Andreas, Abhishek Gupta:
Teachable Reinforcement Learning via Advice Distillation. CoRR abs/2203.11197 (2022) - [i261]Younggyo Seo, Kimin Lee, Stephen James, Pieter Abbeel:
Reinforcement Learning with Action-Free Pre-Training from Videos. CoRR abs/2203.13880 (2022) - [i260]Alejandro Escontrela, Xue Bin Peng, Wenhao Yu, Tingnan Zhang, Atil Iscen, Ken Goldberg, Pieter Abbeel:
Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions. CoRR abs/2203.15103 (2022) - [i259]Kourosh Hakhamaneshi, Marcel Nassar, Mariano Phielipp, Pieter Abbeel, Vladimir Stojanovic:
Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Design. CoRR abs/2203.15913 (2022) - [i258]Stephen James, Pieter Abbeel:
Coarse-to-Fine Q-attention with Learned Path Ranking. CoRR abs/2204.01571 (2022) - [i257]Carl Qi, Pieter Abbeel, Aditya Grover:
Imitating, Fast and Slow: Robust learning from demonstrations via decision-time planning. CoRR abs/2204.03597 (2022) - [i256]Kai Chen, Rui Cao, Stephen James, Yichuan Li, Yun-Hui Liu, Pieter Abbeel, Qi Dou:
Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin-picking. CoRR abs/2204.07049 (2022) - [i255]Stephen James, Pieter Abbeel:
Coarse-to-fine Q-attention with Tree Expansion. CoRR abs/2204.12471 (2022) - [i254]Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah:
An Empirical Investigation of Representation Learning for Imitation. CoRR abs/2205.07886 (2022) - [i253]Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum:
Chain of Thought Imitation with Procedure Cloning. CoRR abs/2205.10816 (2022) - [i252]Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel:
Reward Uncertainty for Exploration in Preference-based Reinforcement Learning. CoRR abs/2205.12401 (2022) - [i251]Xinyang Geng, Hao Liu, Lisa Lee, Dale Schuurams, Sergey Levine, Pieter Abbeel:
Multimodal Masked Autoencoders Learn Transferable Representations. CoRR abs/2205.14204 (2022) - [i250]Mandi Zhao, Pieter Abbeel, Stephen James:
On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning. CoRR abs/2206.03271 (2022) - [i249]Wilson Yan, Ryo Okumura, Stephen James, Pieter Abbeel:
Patch-based Object-centric Transformers for Efficient Video Generation. CoRR abs/2206.04003 (2022) - [i248]Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel:
Deep Hierarchical Planning from Pixels. CoRR abs/2206.04114 (2022) - [i247]Philipp Wu, Alejandro Escontrela, Danijar Hafner, Ken Goldberg, Pieter Abbeel:
DayDreamer: World Models for Physical Robot Learning. CoRR abs/2206.14176 (2022) - [i246]Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel:
Masked World Models for Visual Control. CoRR abs/2206.14244 (2022) - [i245]Ryan Hoque, Lawrence Yunliang Chen, Satvik Sharma, Karthik Dharmarajan, Brijen Thananjeyan, Pieter Abbeel, Ken Goldberg:
Fleet-DAgger: Interactive Robot Fleet Learning with Scalable Human Supervision. CoRR abs/2206.14349 (2022) - [i244]Qiyang Li, Ajay Jain, Pieter Abbeel:
AdaCat: Adaptive Categorical Discretization for Autoregressive Models. CoRR abs/2208.02246 (2022) - [i243]Kyle Hollins Wray, Stas Tiomkin, Mykel J. Kochenderfer, Pieter Abbeel:
Multi-Objective Policy Gradients with Topological Constraints. CoRR abs/2209.07096 (2022) - [i242]Younggyo Seo, Kimin Lee, Fangchen Liu, Stephen James, Pieter Abbeel:
HARP: Autoregressive Latent Video Prediction with High-Fidelity Image Generator. CoRR abs/2209.07143 (2022) - [i241]Litian Liang, Yaosheng Xu, Stephen McAleer, Dailin Hu, Alexander Ihler, Pieter Abbeel, Roy Fox:
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks. CoRR abs/2209.07670 (2022) - [i240]Wilson Yan, Danijar Hafner, Stephen James, Pieter Abbeel:
Temporally Consistent Video Transformer for Long-Term Video Prediction. CoRR abs/2210.02396 (2022) - [i239]Ilija Radosavovic, Tete Xiao, Stephen James, Pieter Abbeel, Jitendra Malik, Trevor Darrell:
Real-World Robot Learning with Masked Visual Pre-training. CoRR abs/2210.03109 (2022) - [i238]Yuxuan Liu, Nikhil Mishra, Maximilian Sieb, Yide Shentu, Pieter Abbeel, Xi Chen:
Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction. CoRR abs/2210.07424 (2022) - [i237]Ademi Adeniji, Amber Xie, Pieter Abbeel:
Skill-Based Reinforcement Learning with Intrinsic Reward Matching. CoRR abs/2210.07426 (2022) - [i236]Abdus Salam Azad, Izzeddin Gur, Aleksandra Faust, Pieter Abbeel, Ion Stoica:
CLUTR: Curriculum Learning via Unsupervised Task Representation Learning. CoRR abs/2210.10243 (2022) - [i235]Weirui Ye, Pieter Abbeel, Yang Gao:
Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions. CoRR abs/2210.12628 (2022) - [i234]Hao Liu, Lisa Lee, Kimin Lee, Pieter Abbeel:
Instruction-Following Agents with Jointly Pre-Trained Vision-Language Models. CoRR abs/2210.13431 (2022) - [i233]Hao Liu, Xinyang Geng, Lisa Lee, Igor Mordatch, Sergey Levine, Sharan Narang, Pieter Abbeel:
FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners. CoRR abs/2210.13432 (2022) - [i232]Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum:
Dichotomy of Control: Separating What You Can Control from What You Cannot. CoRR abs/2210.13435 (2022) - [i231]John So, Amber Xie, Sunggoo Jung, Jeffrey A. Edlund, Rohan Thakker, Ali-Akbar Agha-Mohammadi, Pieter Abbeel, Stephen James:
Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real Data. CoRR abs/2210.14721 (2022) - [i230]Kai Chen, Stephen James, Congying Sui, Yun-Hui Liu, Pieter Abbeel, Qi Dou:
StereoPose: Category-Level 6D Transparent Object Pose Estimation from Stereo Images via Back-View NOCS. CoRR abs/2211.01644 (2022) - [i229]Ajay Jain, Amber Xie, Pieter Abbeel:
VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models. CoRR abs/2211.11319 (2022) - [i228]Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel:
Masked Autoencoding for Scalable and Generalizable Decision Making. CoRR abs/2211.12740 (2022) - [i227]David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum:
Multi-Environment Pretraining Enables Transfer to Action Limited Datasets. CoRR abs/2211.13337 (2022) - 2021
- [j25]Gregory Kahn, Pieter Abbeel, Sergey Levine:
BADGR: An Autonomous Self-Supervised Learning-Based Navigation System. IEEE Robotics Autom. Lett. 6(2): 1312-1319 (2021) - [j24]Gregory Kahn, Pieter Abbeel, Sergey Levine:
LaND: Learning to Navigate From Disengagements. IEEE Robotics Autom. Lett. 6(2): 1872-1879 (2021) - [j23]Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, Angjoo Kanazawa:
AMP: adversarial motion priors for stylized physics-based character control. ACM Trans. Graph. 40(4): 144:1-144:20 (2021) - [c261]Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin:
Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback. CoRL 2021: 1259-1268 - [c260]Seunghyun Lee, Younggyo Seo, Kimin Lee, Pieter Abbeel, Jinwoo Shin:
Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble. CoRL 2021: 1702-1712 - [c259]Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani:
Bottleneck Transformers for Visual Recognition. CVPR 2021: 16519-16529 - [c258]Paras Jain, Ajay Jain, Tianjun Zhang, Pieter Abbeel, Joseph Gonzalez, Ion Stoica:
Contrastive Code Representation Learning. EMNLP (1) 2021: 5954-5971 - [c257]Ajay Jain, Matthew Tancik, Pieter Abbeel:
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis. ICCV 2021: 5865-5874 - [c256]Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin:
Efficient Empowerment Estimation for Unsupervised Stabilization. ICLR 2021 - [c255]Nicklas Hansen, Rishabh Jangir, Yu Sun, Guillem Alenyà, Pieter Abbeel, Alexei A. Efros, Lerrel Pinto, Xiaolong Wang:
Self-Supervised Policy Adaptation during Deployment. ICLR 2021 - [c254]Donald Joseph Hejna III, Pieter Abbeel, Lerrel Pinto:
Task-Agnostic Morphology Evolution. ICLR 2021 - [c253]David Lindner, Rohin Shah, Pieter Abbeel, Anca D. Dragan:
Learning What To Do by Simulating the Past. ICLR 2021 - [c252]Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch:
Reset-Free Lifelong Learning with Skill-Space Planning. ICLR 2021 - [c251]Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu:
Mutual Information State Intrinsic Control. ICLR 2021 - [c250]Boyuan Chen, Pieter Abbeel, Deepak Pathak:
Unsupervised Learning of Visual 3D Keypoints for Control. ICML 2021: 1539-1549 - [c249]Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel:
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. ICML 2021: 6131-6141 - [c248]Kimin Lee, Laura M. Smith, Pieter Abbeel:
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training. ICML 2021: 6152-6163 - [c247]Hao Liu, Pieter Abbeel:
APS: Active Pretraining with Successor Features. ICML 2021: 6736-6747 - [c246]Roshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John F. Canny, Pieter Abbeel, Tom Sercu, Alexander Rives:
MSA Transformer. ICML 2021: 8844-8856 - [c245]Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
State Entropy Maximization with Random Encoders for Efficient Exploration. ICML 2021: 9443-9454 - [c244]Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin:
Decoupling Representation Learning from Reinforcement Learning. ICML 2021: 9870-9879 - [c243]Yuqing Du, Olivia Watkins, Trevor Darrell, Pieter Abbeel, Deepak Pathak:
Auto-Tuned Sim-to-Real Transfer. ICRA 2021: 1290-1296 - [c242]Zhongyu Li, Xuxin Cheng, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath:
Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots. ICRA 2021: 2811-2817 - [c241]Cynthia Chen, Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah:
An Empirical Investigation of Representation Learning for Imitation. NeurIPS Datasets and Benchmarks 2021 - [c240]Charles Packer, Pieter Abbeel, Joseph E. Gonzalez:
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL. NeurIPS 2021: 2466-2477 - [c239]Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas:
Teachable Reinforcement Learning via Advice Distillation. NeurIPS 2021: 6920-6933 - [c238]Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch:
Decision Transformer: Reinforcement Learning via Sequence Modeling. NeurIPS 2021: 15084-15097 - [c237]