Active inference: demystified and compared N Sajid, PJ Ball, T Parr, KJ Friston Neural Computation 33 (3), 2021 | 156* | 2021 |
Efficient Online Reinforcement Learning with Offline Data PJ Ball*, L Smith*, I Kostrikov*, S Levine ICML 2023, 2023 | 73 | 2023 |
The sensitivity of counterfactual fairness to unmeasured confounding N Kilbertus, PJ Ball, MJ Kusner, A Weller, R Silva UAI 2019, 2019 | 64 | 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 | 54* | 2022 |
Ready policy one: World building through active learning P Ball*, J Parker-Holder*, A Pacchiano, K Choromanski, S Roberts ICML 2020, 2020 | 53 | 2020 |
Same State, Different Task: Continual Reinforcement Learning without Interference S Kessler, J Parker-Holder, P Ball, S Zohren, SJ Roberts AAAI-22, 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 | 40* | 2021 |
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 | 37 | 2023 |
Synthetic Experience Replay C Lu*, PJ Ball*, J Parker-Holder NeurIPS 2023, 2023 | 32 | 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 | 32 | 2021 |
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels E Cetin*, PJ Ball*, S Roberts, O Celiktutan ICML 2022, 2022 | 27 | 2022 |
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 | 20 | 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 | 8 | 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 | 6 | 2020 |
OffCon: What is state of the art anyway? PJ Ball, SJ Roberts arXiv preprint arXiv:2101.11331, 2021 | 5 | 2021 |
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 |
D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning R Rafailov, KB Hatch, A Singh, A Kumar, L Smith, I Kostrikov, ... | | |