Philip J. Ball

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Jack Parker-HolderGoogle DeepMind, UCLEmail confirmado em google.com
Stephen RobertsProfessor of Engineering Science (Machine Learning, Information Engineering), University of OxfordEmail confirmado em robots.ox.ac.uk
Cong LuUniversity of British ColumbiaEmail confirmado em cs.ubc.ca
Karl FristonUniversity College LondonEmail confirmado em ucl.ac.uk
Aldo PacchianoBroad Institute of MIT and HarvardEmail confirmado em broadinstitute.org
Ilya KostrikovOpenAIEmail confirmado em openai.com
Michael A OsborneProfessor of Machine Learning, University of OxfordEmail confirmado em robots.ox.ac.uk
Krzysztof ChoromanskiGoogle DeepMind Robotics & Columbia UniversityEmail confirmado em columbia.edu
Sergey LevineUC Berkeley, Physical IntelligenceEmail confirmado em eecs.berkeley.edu
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindEmail confirmado em stats.ox.ac.uk
Laura SmithUC BerkeleyEmail confirmado em berkeley.edu
Samuel KesslerUniversity of OxfordEmail confirmado em robots.ox.ac.uk
Adrian WellerDirector of Research, Machine Learning, University of CambridgeEmail confirmado em eng.cam.ac.uk
Tim G. J. RudnerFaculty Fellow, New York UniversityEmail confirmado em nyu.edu
Xingchen WanGoogleEmail confirmado em google.com
Tim RocktäschelDirector and Open-Endedness Team Lead at Google DeepMind, Professor of AI at UCL, Fellow ELLISEmail confirmado em cs.ucl.ac.uk
Oleh RybkinPostdoc, University of California, BerkeleyEmail confirmado em seas.upenn.edu

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Philip J. Ball

Google DeepMind

Email confirmado em google.com - Página inicial

machine learning reinforcement learning data efficiency diffusion models


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Active inference: demystified and compared N Sajid, PJ Ball, T Parr, KJ Friston Neural Computation 33 (3), 2021	185	2021
Efficient Online Reinforcement Learning with Offline Data PJ Ball, L Smith, I Kostrikov*, S Levine ICML 2023, 2023	128	2023
The sensitivity of counterfactual fairness to unmeasured confounding N Kilbertus, PJ Ball, MJ Kusner, A Weller, R Silva UAI 2019, 2019	67	2019
Revisiting Design Choices in Model-Based Offline Reinforcement Learning C Lu, PJ Ball, J Parker-Holder, MA Osborne, SJ Roberts ICLR 2022 (Spotlight), 2022	65*	2022
Ready policy one: World building through active learning P Ball, J Parker-Holder, A Pacchiano, K Choromanski, S Roberts ICML 2020, 2020	56	2020
Synthetic Experience Replay C Lu, PJ Ball, J Parker-Holder NeurIPS 2023, 2023	52	2023
Same State, Different Task: Continual Reinforcement Learning without Interference S Kessler, J Parker-Holder, P Ball, S Zohren, SJ Roberts AAAI-22, 2022	47	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	44	2023
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels E Cetin, PJ Ball, S Roberts, O Celiktutan ICML 2022, 2022	41	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
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	40	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	22	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	9	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	5	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	2	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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