Philip J. Ball

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Jack Parker-HolderGoogle DeepMind, UCLVerificeret mail på google.com
Stephen RobertsProfessor of Engineering Science (Machine Learning, Information Engineering), University of OxfordVerificeret mail på robots.ox.ac.uk
Cong LuGoogle DeepMindVerificeret mail på google.com
Karl FristonUniversity College LondonVerificeret mail på ucl.ac.uk
Aldo PacchianoBoston University and Broad Institute of MIT and HarvardVerificeret mail på bu.edu
Ilya KostrikovOpenAIVerificeret mail på openai.com
Michael A OsborneProfessor of Machine Learning, University of OxfordVerificeret mail på robots.ox.ac.uk
Krzysztof ChoromanskiGoogle DeepMind Robotics & Columbia UniversityVerificeret mail på columbia.edu
Sergey LevineUC Berkeley, Physical IntelligenceVerificeret mail på eecs.berkeley.edu
Laura SmithUC BerkeleyVerificeret mail på berkeley.edu
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerificeret mail på stats.ox.ac.uk
Samuel KesslerUniversity of OxfordVerificeret mail på robots.ox.ac.uk
Adrian WellerDirector of Research, Machine Learning, University of CambridgeVerificeret mail på eng.cam.ac.uk
Tim G. J. RudnerFaculty Fellow, New York UniversityVerificeret mail på nyu.edu
Xingchen WanGoogleVerificeret mail på google.com
Tim RocktäschelDirector and Open-Endedness Team Lead at Google DeepMind, Professor of AI at UCL, Fellow ELLISVerificeret mail på cs.ucl.ac.uk
Oleh RybkinPostdoc, University of California, BerkeleyVerificeret mail på seas.upenn.edu

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Philip J. Ball

Google DeepMind

Verificeret mail på google.com - Startside

machine learning reinforcement learning data efficiency diffusion models


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
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	160	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
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels E Cetin, PJ Ball, S Roberts, O Celiktutan ICML 2022, 2022	43	2022
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	43	2021
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	8	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
Genie 2: A Large-Scale Foundation World Model https://deepmind.google/discover/blog/genie-2-a-large-scale-foundation-world …, 2024		2024
Effective offline training and efficient online adaptation P Ball University of Oxford, 2023		2023

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