Pieter Abbeel

Natural Image Manipulation for Autoregressive Models Using Fisher Scores

Wilson Yan, Jonathan Ho, Pieter Abbeel

Plan2Vec: Unsupervised Representation Learning by Latent Plans

Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra

Comments code available at https://geyang.github.io/plan2vec

Journal ref Proceedings of Machine Learning Research, the 2nd Annual Conference on Learning for Dynamics and Control (2020) Volume 120, 1-12

BADGR: An Autonomous Self-Supervised Learning-Based Navigation System

Gregory Kahn, Pieter Abbeel, Sergey Levine

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch

Learning Predictive Representations for Deformable Objects Using Contrastive Estimation

Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto

Comments Project website: https://sites.google.com/view/contrastive-predictive-model

Learning to Manipulate Deformable Objects without Demonstrations

Yilin Wu, Wilson Yan, Thanard Kurutach, Lerrel Pinto, Pieter Abbeel

Comments Project website: https://sites.google.com/view/alternating-pick-and-place

Hallucinative Topological Memory for Zero-Shot Visual Planning

Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar

Generalized Hindsight for Reinforcement Learning

Alexander C. Li, Lerrel Pinto, Pieter Abbeel

GACEM: Generalized Autoregressive Cross Entropy Method for Multi-Modal Black Box Constraint Satisfaction

Kourosh Hakhamaneshi, Keertana Settaluri, Pieter Abbeel, Vladimir Stojanovic

On the Utility of Learning about Humans for Human-AI Coordination

Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca Dragan

Comments Published at NeurIPS 2019 (http://papers.nips.cc/paper/8760-on-the-utility-of-learning-about-humans-for-human-ai-coordination)

Compression with Flows via Local Bits-Back Coding

Jonathan Ho, Evan Lohn, Pieter Abbeel

Comments Published in NeurIPS 2019

Hierarchical Variational Imitation Learning of Control Programs

Roy Fox, Richard Shin, William Paul, Yitian Zou, Dawn Song, Ken Goldberg, Pieter Abbeel, Ion Stoica

Deep Unsupervised Cardinality Estimation

Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica

Comments VLDB 2020. Updates since version 1: new title and new/revised content

Journal ref Proceedings of the VLDB Endowment (PLVDB), Vol. 13, No. 3, pp. 279-292 (2019)

Geometry-Aware Neural Rendering

Josh Tobin, OpenAI Robotics, Pieter Abbeel

Comments 16 pages, 13 figures

Journal ref 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada

Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs

Himanshu Sahni, Toby Buckley, Pieter Abbeel, Ilya Kuzovkin

Comments To appear in Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. Code available at https://github.com/offworld-projects/research-halgan

Asynchronous Methods for Model-Based Reinforcement Learning

Yunzhi Zhang, Ignasi Clavera, Boren Tsai, Pieter Abbeel

Comments 10 pages, CoRL 2019

Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables

Friso H. Kingma, Pieter Abbeel, Jonathan Ho

Comments Accepted to ICML 2019

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

Adam Stooke, Pieter Abbeel

Comments v2: Updated learning curves for SAC and TD3, improved by bootstrapping value-function when trajectory ends due to time limit, and switching to newer SAC version, now referenced

Third-Person Imitation Learning

Bradly C. Stadie, Pieter Abbeel, Ilya Sutskever

Comments Only changed the abstract to remove unneeded hyphens

Soft Actor-Critic Algorithms and Applications

Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, Sergey Levine

Comments arXiv admin note: substantial text overlap with arXiv:1801.01290

BagNet: Berkeley Analog Generator with Layout Optimizer Boosted with Deep Neural Networks

Kourosh Hakhamaneshi, Nick Werblun, Pieter Abbeel, Vladimir Stojanovic

Comments Accepted on ICCAD 2019 Conference

Benchmarking Model-Based Reinforcement Learning

Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba

Comments 8 main pages, 8 figures; 14 appendix pages, 25 figures

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference

Rohin Shah, Noah Gundotra, Pieter Abbeel, Anca D. Dragan

Comments Published at ICML 2019

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning

Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew J. Johnson, Sergey Levine

Comments ICML 2019. Project website: https://sites.google.com/view/icml19solar

Evaluating Protein Transfer Learning with TAPE

Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Xi Chen, John Canny, Pieter Abbeel, Yun S. Song

Comments 20 pages, 4 figures

Learning latent state representation for speeding up exploration

Giulia Vezzani, Abhishek Gupta, Lorenzo Natale, Pieter Abbeel

Comments 7 pages, 8 figures, workshop

Journal ref 2nd Exploration in Reinforcement Learning Workshop at the 36 th International Conference on Machine Learning, 2019

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies

Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design

Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel

Comments Accepted at ICML 2019

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules

Daniel Ho, Eric Liang, Ion Stoica, Pieter Abbeel, Xi Chen

Comments ICML 2019

Learning Robotic Manipulation through Visual Planning and Acting

Angelina Wang, Thanard Kurutach, Kara Liu, Pieter Abbeel, Aviv Tamar

Comments RSS 2019. Website at https://sites.google.com/berkeley.edu/vpa/home