Philip J. Ball

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Jack Parker-HolderGoogle DeepMind, UCL確認したメールアドレス: google.com
Stephen RobertsProfessor of Engineering Science (Machine Learning, Information Engineering), University of Oxford確認したメールアドレス: robots.ox.ac.uk
Cong LuUniversity of British Columbia確認したメールアドレス: cs.ubc.ca
Karl FristonUniversity College London確認したメールアドレス: ucl.ac.uk
Aldo PacchianoBoston University and Broad Institute of MIT and Harvard確認したメールアドレス: bu.edu
Ilya KostrikovOpenAI確認したメールアドレス: openai.com
Michael A OsborneProfessor of Machine Learning, University of Oxford確認したメールアドレス: robots.ox.ac.uk
Krzysztof ChoromanskiGoogle DeepMind Robotics & Columbia University確認したメールアドレス: columbia.edu
Sergey LevineUC Berkeley, Physical Intelligence確認したメールアドレス: eecs.berkeley.edu
Laura SmithUC Berkeley確認したメールアドレス: berkeley.edu
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMind確認したメールアドレス: stats.ox.ac.uk
Samuel KesslerUniversity of Oxford確認したメールアドレス: robots.ox.ac.uk
Adrian WellerDirector of Research, Machine Learning, University of Cambridge確認したメールアドレス: eng.cam.ac.uk
Tim G. J. RudnerFaculty Fellow, New York University確認したメールアドレス: nyu.edu
Xingchen WanGoogle確認したメールアドレス: google.com
Tim RocktäschelDirector and Open-Endedness Team Lead at Google DeepMind, Professor of AI at UCL, Fellow ELLIS確認したメールアドレス: cs.ucl.ac.uk
Oleh RybkinPostdoc, University of California, Berkeley確認したメールアドレス: seas.upenn.edu

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Philip J. Ball

Google DeepMind

確認したメールアドレス: google.com - ホームページ

machine learning reinforcement learning data efficiency diffusion models


タイトル引用回数順公開年順タイトル順	引用先引用先	年
Active inference: demystified and compared N Sajid, PJ Ball, T Parr, KJ Friston Neural Computation 33 (3), 2021	196	2021
Efficient Online Reinforcement Learning with Offline Data PJ Ball, L Smith, I Kostrikov*, S Levine ICML 2023, 2023	151	2023
Revisiting Design Choices in Model-Based Offline Reinforcement Learning C Lu, PJ Ball, J Parker-Holder, MA Osborne, SJ Roberts ICLR 2022 (Spotlight), 2022	70*	2022
The sensitivity of counterfactual fairness to unmeasured confounding N Kilbertus, PJ Ball, MJ Kusner, A Weller, R Silva UAI 2019, 2019	69	2019
Synthetic Experience Replay C Lu, PJ Ball, J Parker-Holder NeurIPS 2023, 2023	63	2023
Ready policy one: World building through active learning P Ball, J Parker-Holder, A Pacchiano, K Choromanski, S Roberts ICML 2020, 2020	57	2020
Same State, Different Task: Continual Reinforcement Learning without Interference S Kessler, J Parker-Holder, P Ball, S Zohren, SJ Roberts AAAI-22, 2022	48	2022
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations C Lu, PJ Ball, TGJ Rudner, J Parker-Holder, MA Osborne, YW Teh TMLR, 2023	47	2023
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment PJ Ball, C Lu, J Parker-Holder, S Roberts ICML 2021, 2021	44	2021
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels E Cetin, PJ Ball, S Roberts, O Celiktutan ICML 2022, 2022	43	2022
Towards Tractable Optimism in Model-Based Reinforcement Learning A Pacchiano, P Ball, J Parker-Holder*, K Choromanski, S Roberts UAI 2021, 2021	41*	2021
Bayesian Generational Population-Based Training X Wan, C Lu, J Parker-Holder, PJ Ball, V Nguyen, B Ru, M Osborne First Conference on Automated Machine Learning (Main Track), 2022	23	2022
Learning General World Models in a Handful of Reward-Free Deployments Y Xu, J Parker-Holder, A Pacchiano, PJ Ball, O Rybkin, SJ Roberts, ... NeurIPS 2022, 2022	10	2022
UNCLEAR: A Straightforward Method for Continual Reinforcement Learning S Kessler, J Parker-Holder, P Ball, S Zohren, SJ Roberts ICML 2020 Workshop on Continual Learning, 2020	7	2020
OffCon: What is state of the art anyway? PJ Ball, SJ Roberts arXiv preprint arXiv:2101.11331, 2021	6	2021
D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning R Rafailov, K Hatch, A Singh, L Smith, A Kumar, I Kostrikov, ... arXiv preprint arXiv:2408.08441, 2024	4	2024
A Study on Efficiency in Continual Learning Inspired by Human Learning PJ Ball, Y Li, A Lamb, C Zhang NeurIPS 2020 BabyMind Workshop, 2020	2	2020
Fairness in Machine Learning with Causal Reasoning P Ball MPhil Thesis, 2018	1	2018
Effective offline training and efficient online adaptation P Ball University of Oxford, 2023		2023

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