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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
- 2022
[i242]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)- [i241]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) - [i240]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) - [i239]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) - [i238]Stephen James, Pieter Abbeel:
Bingham Policy Parameterization for 3D Rotations in Reinforcement Learning. CoRR abs/2202.03957 (2022) - [i237]Yuqing Du, Pieter Abbeel, Aditya Grover:
It Takes Four to Tango: Multiagent Selfplay for Automatic Curriculum Generation. CoRR abs/2202.10608 (2022) - [i236]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) - [i235]Olivia Watkins, Trevor Darrell, Pieter Abbeel, Jacob Andreas, Abhishek Gupta:
Teachable Reinforcement Learning via Advice Distillation. CoRR abs/2203.11197 (2022) - [i234]Younggyo Seo, Kimin Lee, Stephen James, Pieter Abbeel:
Reinforcement Learning with Action-Free Pre-Training from Videos. CoRR abs/2203.13880 (2022) - [i233]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) - [i232]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) - [i231]Stephen James, Pieter Abbeel:
Coarse-to-Fine Q-attention with Learned Path Ranking. CoRR abs/2204.01571 (2022) - [i230]Carl Qi, Pieter Abbeel, Aditya Grover:
Imitating, Fast and Slow: Robust learning from demonstrations via decision-time planning. CoRR abs/2204.03597 (2022) - [i229]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) - [i228]Stephen James, Pieter Abbeel:
Coarse-to-fine Q-attention with Tree Expansion. CoRR abs/2204.12471 (2022) - [i227]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) - 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]Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel:
URLB: Unsupervised Reinforcement Learning Benchmark. NeurIPS Datasets and Benchmarks 2021 - [c239]Charles Packer, Pieter Abbeel, Joseph E. Gonzalez:
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL. NeurIPS 2021: 2466-2477 - [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]Kimin Lee, Laura Smith, Anca D. Dragan, Pieter Abbeel:
B-Pref: Benchmarking Preference-Based Reinforcement Learning. NeurIPS Datasets and Benchmarks 2021 - [c236]Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas:
Teachable Reinforcement Learning via Advice Distillation. NeurIPS 2021: 6920-6933 - [c235]Hao Liu, Pieter Abbeel:
Behavior From the Void: Unsupervised Active Pre-Training. NeurIPS 2021: 18459-18473 - [c234]Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin:
Reinforcement Learning with Latent Flow. NeurIPS 2021: 22171-22183 - [c233]Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao:
Mastering Atari Games with Limited Data. NeurIPS 2021: 25476-25488 - [c232]Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel:
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. NeurIPS 2021: 26779-26791 - [i226]Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin:
Reinforcement Learning with Latent Flow. CoRR abs/2101.01857 (2021) - [i225]Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani:
Bottleneck Transformers for Visual Recognition. CoRR abs/2101.11605 (2021) - [i224]Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
State Entropy Maximization with Random Encoders for Efficient Exploration. CoRR abs/2102.09430 (2021) - [i223]Donald J. Hejna III, Pieter Abbeel, Lerrel Pinto:
Task-Agnostic Morphology Evolution. CoRR abs/2102.13100 (2021) - [i222]Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel:
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. CoRR abs/2103.02886 (2021) - [i221]Hao Liu, Pieter Abbeel:
Behavior From the Void: Unsupervised Active Pre-Training. CoRR abs/2103.04551 (2021) - [i220]Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch:
Pretrained Transformers as Universal Computation Engines. CoRR abs/2103.05247 (2021) - [i219]Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu:
Mutual Information State Intrinsic Control. CoRR abs/2103.08107 (2021) - [i218]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. CoRR abs/2103.14295 (2021) - [i217]Ajay Jain, Matthew Tancik, Pieter Abbeel:
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis. CoRR abs/2104.00677 (2021) - [i216]Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, Angjoo Kanazawa:
AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control. CoRR abs/2104.02180 (2021) - [i215]Philippe Hansen-Estruch, Wenling Shang, Lerrel Pinto, Pieter Abbeel, Stas Tiomkin:
GEM: Group Enhanced Model for Learning Dynamical Control Systems. CoRR abs/2104.02844 (2021) - [i214]David Lindner, Rohin Shah, Pieter Abbeel, Anca D. Dragan:
Learning What To Do by Simulating the Past. CoRR abs/2104.03946 (2021) - [i213]Yuqing Du, Olivia Watkins, Trevor Darrell, Pieter Abbeel, Deepak Pathak:
Auto-Tuned Sim-to-Real Transfer. CoRR abs/2104.07662 (2021) - [i212]Wilson Yan, Yunzhi Zhang, Pieter Abbeel, Aravind Srinivas:
VideoGPT: Video Generation using VQ-VAE and Transformers. CoRR abs/2104.10157 (2021) - [i211]Kourosh Hakhamaneshi, Pieter Abbeel, Vladimir Stojanovic, Aditya Grover:
JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data. CoRR abs/2106.00942 (2021) - [i210]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. CoRR abs/2106.01345 (2021) - [i209]Kimin Lee, Laura M. Smith, Pieter Abbeel:
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training. CoRR abs/2106.05091 (2021) - [i208]Boyuan Chen, Pieter Abbeel, Deepak Pathak:
Unsupervised Learning of Visual 3D Keypoints for Control. CoRR abs/2106.07643 (2021) - [i207]Catherine Cang, Aravind Rajeswaran, Pieter Abbeel, Michael Laskin:
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL. CoRR abs/2106.09119 (2021) - [i206]Abdus Salam Azad, Edward Kim, Qiancheng Wu, Kimin Lee, Ion Stoica, Pieter Abbeel, Sanjit A. Seshia:
Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments. CoRR abs/2106.10365 (2021) - [i205]Seunghyun Lee, Younggyo Seo, Kimin Lee, Pieter Abbeel, Jinwoo Shin:
Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble. CoRR abs/2107.00591 (2021) - [i204]Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca D. Dragan:
The MineRL BASALT Competition on Learning from Human Feedback. CoRR abs/2107.01969 (2021) - [i203]Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin:
Hierarchical Few-Shot Imitation with Skill Transition Models. CoRR abs/2107.08981 (2021) - [i202]Sarah Young, Jyothish Pari, Pieter Abbeel, Lerrel Pinto:
Playful Interactions for Representation Learning. CoRR abs/2107.09046 (2021) - [i201]Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin:
Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback. CoRR abs/2108.05382 (2021) - [i200]Hao Liu, Pieter Abbeel:
APS: Active Pretraining with Successor Features. CoRR abs/2108.13956 (2021) - [i199]Mandi Zhao, Fangchen Liu, Kimin Lee, Pieter Abbeel:
Towards More Generalizable One-shot Visual Imitation Learning. CoRR abs/2110.13423 (2021) - [i198]Litian Liang, Yaosheng Xu, Stephen McAleer, Dailin Hu, Alexander Ihler, Pieter Abbeel, Roy Fox:
Temporal-Difference Value Estimation via Uncertainty-Guided Soft Updates. CoRR abs/2110.14818 (2021) - [i197]Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel:
URLB: Unsupervised Reinforcement Learning Benchmark. CoRR abs/2110.15191 (2021) - [i196]Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao:
Mastering Atari Games with Limited Data. CoRR abs/2111.00210 (2021) - [i195]Kimin Lee, Laura Smith, Anca D. Dragan, Pieter Abbeel:
B-Pref: Benchmarking Preference-Based Reinforcement Learning. CoRR abs/2111.03026 (2021) - [i194]Wenlong Huang, Igor Mordatch, Pieter Abbeel, Deepak Pathak:
Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning. CoRR abs/2111.03062 (2021) - [i193]Dailin Hu, Pieter Abbeel, Roy Fox:
Count-Based Temperature Scheduling for Maximum Entropy Reinforcement Learning. CoRR abs/2111.14204 (2021) - [i192]Charles Packer, Pieter Abbeel, Joseph E. Gonzalez:
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL. CoRR abs/2112.00901 (2021) - [i191]Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole:
Zero-Shot Text-Guided Object Generation with Dream Fields. CoRR abs/2112.01455 (2021) - [i190]Yaosheng Xu, Dailin Hu, Litian Liang, Stephen McAleer, Pieter Abbeel, Roy Fox:
Target Entropy Annealing for Discrete Soft Actor-Critic. CoRR abs/2112.02852 (2021) - 2020
- [c231]Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto:
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation. CoRL 2020: 564-574 - [c230]Sarah Young, Dhiraj Gandhi, Shubham Tulsiani, Abhinav Gupta, Pieter Abbeel, Lerrel Pinto:
Visual Imitation Made Easy. CoRL 2020: 1992-2005 - [c229]Ignasi Clavera, Yao Fu, Pieter Abbeel:
Model-Augmented Actor-Critic: Backpropagating through Paths. ICLR 2020 - [c228]Alexander C. Li, Carlos Florensa, Ignasi Clavera, Pieter Abbeel:
Sub-policy Adaptation for Hierarchical Reinforcement Learning. ICLR 2020 - [c227]Donald J. Hejna III, Lerrel Pinto, Pieter Abbeel:
Hierarchically Decoupled Imitation For Morphological Transfer. ICML 2020: 4159-4171 - [c226]Michael Laskin, Aravind Srinivas, Pieter Abbeel:
CURL: Contrastive Unsupervised Representations for Reinforcement Learning. ICML 2020: 5639-5650 - [c225]Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Xi Chen:
Variable Skipping for Autoregressive Range Density Estimation. ICML 2020: 6040-6049 - [c224]Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar:
Hallucinative Topological Memory for Zero-Shot Visual Planning. ICML 2020: 6259-6270 - [c223]Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak:
Planning to Explore via Self-Supervised World Models. ICML 2020: 8583-8592 - [c222]Adam Stooke, Joshua Achiam, Pieter Abbeel:
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods. ICML 2020: 9133-9143 - [c221]Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra:
Plan2Vec: Unsupervised Representation Learning by Latent Plans. L4DC 2020: 935-946 - [c220]Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph Gonzalez:
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. MLSys 2020 - [c219]Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca D. Dragan:
AvE: Assistance via Empowerment. NeurIPS 2020 - [c218]Scott Emmons, Ajay Jain, Michael Laskin, Thanard Kurutach, Pieter Abbeel, Deepak Pathak:
Sparse Graphical Memory for Robust Planning. NeurIPS 2020 - [c217]Jonathan Ho, Ajay Jain, Pieter Abbeel:
Denoising Diffusion Probabilistic Models. NeurIPS 2020 - [c216]Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas:
Reinforcement Learning with Augmented Data. NeurIPS 2020 - [c215]Alex X. Lee, Anusha Nagabandi, Pieter Abbeel, Sergey Levine:
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model. NeurIPS 2020 - [c214]Alexander C. Li, Lerrel Pinto, Pieter Abbeel:
Generalized Hindsight for Reinforcement Learning. NeurIPS 2020 - [c213]Younggyo Seo, Kimin Lee, Ignasi Clavera Gilaberte, Thanard Kurutach, Jinwoo Shin, Pieter Abbeel:
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning. NeurIPS 2020 - [c212]Yunzhi Zhang, Pieter Abbeel, Lerrel Pinto:
Automatic Curriculum Learning through Value Disagreement. NeurIPS 2020 - [c211]Laura Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine:
AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos. Robotics: Science and Systems 2020 - [c210]Yilin Wu, Wilson Yan, Thanard Kurutach, Lerrel Pinto, Pieter Abbeel:
Learning to Manipulate Deformable Objects without Demonstrations. Robotics: Science and Systems 2020 - [c209]Ajay Jain, Pieter Abbeel, Deepak Pathak:
Locally Masked Convolution for Autoregressive Models. UAI 2020: 1358-1367 - [e2]Ken Goldberg, Pieter Abbeel, Kostas E. Bekris, Lauren Miller:
Algorithmic Foundations of Robotics XII, Proceedings of the Twelfth Workshop on the Algorithmic Foundations of Robotics, WAFR 2016, San Francisco, California, USA, December 18-20, 2016. Springer Proceedings in Advanced Robotics 13, Springer 2020, ISBN 978-3-030-43088-7 [contents] - [i189]Albert Zhan, Stas Tiomkin, Pieter Abbeel:
Preventing Imitation Learning with Adversarial Policy Ensembles. CoRR abs/2002.01059 (2020) - [i188]Gregory Kahn, Pieter Abbeel, Sergey Levine:
BADGR: An Autonomous Self-Supervised Learning-Based Navigation System. CoRR abs/2002.05700 (2020) - [i187]Kourosh Hakhamaneshi, Keertana Settaluri, Pieter Abbeel, Vladimir Stojanovic:
GACEM: Generalized Autoregressive Cross Entropy Method for Multi-Modal Black Box Constraint Satisfaction. CoRR abs/2002.07236 (2020) - [i186]Alexander C. Li, Lerrel Pinto, Pieter Abbeel:
Generalized Hindsight for Reinforcement Learning. CoRR abs/2002.11708 (2020) - [i185]Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar:
Hallucinative Topological Memory for Zero-Shot Visual Planning. CoRR abs/2002.12336 (2020) - [i184]Donald J. Hejna III, Pieter Abbeel, Lerrel Pinto:
Hierarchically Decoupled Imitation for Morphological Transfer. CoRR abs/2003.01709 (2020) - [i183]Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto:
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation. CoRR abs/2003.05436 (2020) - [i182]Michael Laskin, Scott Emmons, Ajay Jain, Thanard Kurutach, Pieter Abbeel, Deepak Pathak:
Sparse Graphical Memory for Robust Planning. CoRR abs/2003.06417 (2020) - [i181]Aravind Srinivas, Michael Laskin, Pieter Abbeel:
CURL: Contrastive Unsupervised Representations for Reinforcement Learning. CoRR abs/2004.04136 (2020) - [i180]Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas:
Reinforcement Learning with Augmented Data. CoRR abs/2004.14990 (2020) - [i179]Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra:
Plan2Vec: Unsupervised Representation Learning by Latent Plans. CoRR abs/2005.03648 (2020) - [i178]Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak:
Planning to Explore via Self-Supervised World Models. CoRR abs/2005.05960 (2020) - [i177]Ignasi Clavera, Violet Fu, Pieter Abbeel:
Model-Augmented Actor-Critic: Backpropagating through Paths. CoRR abs/2005.08068 (2020) - [i176]