Philip J. Ball
Philip J. Ball
DPhil Student Machine Learning, University of Oxford
Verified email at - Homepage
Cited by
Cited by
Active inference: demystified and compared
N Sajid, PJ Ball, T Parr, KJ Friston
Neural Computation 33 (3), 2021
The sensitivity of counterfactual fairness to unmeasured confounding
N Kilbertus, PJ Ball, MJ Kusner, A Weller, R Silva
UAI 2019, 2019
Ready policy one: World building through active learning
P Ball, J Parker-Holder, A Pacchiano, K Choromanski, S Roberts
ICML 2020, 2020
Towards Tractable Optimism in Model-Based Reinforcement Learning
A Pacchiano*, P Ball*, J Parker-Holder*, K Choromanski, S Roberts
UAI 2021, 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
Revisiting Design Choices in Model-Based Offline Reinforcement Learning
C Lu*, PJ Ball*, J Parker-Holder, MA Osborne, SJ Roberts
ICLR2022, 2022
Same State, Different Task: Continual Reinforcement Learning without Interference
S Kessler, J Parker-Holder, P Ball, S Zohren, SJ Roberts
AAAI-22, 2022
OffCon: What is state of the art anyway?
PJ Ball, SJ Roberts
arXiv preprint arXiv:2101.11331, 2021
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
A Study on Efficiency in Continual Learning Inspired by Human Learning
PJ Ball, Y Li, A Lamb, C Zhang
NeurIPS 2020 BabyMind Workshop, 2020
Fairness in Machine Learning with Causal Reasoning
P Ball
MPhil Thesis, 2018
The system can't perform the operation now. Try again later.
Articles 1–11