Philip J. Ball

According to our database, Philip J. Ball authored at least 20 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning.

Rafael Rafailov, Kyle Beltran Hatch, Anikait Singh, Aviral Kumar, Laura M. Smith, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Sergey Levine, Chelsea Finn

RLJ, 2024

2023

Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations.

Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh

Trans. Mach. Learn. Res., 2023

Synthetic Experience Replay.

Cong Lu, Philip J. Ball, Jack Parker-Holder

CoRR, 2023

Synthetic Experience Replay.

Cong Lu, Philip J. Ball, Yee Whye Teh, Jack Parker-Holder

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Online Reinforcement Learning with Offline Data.

Philip J. Ball, Laura M. Smith, Ilya Kostrikov, Sergey Levine

Proceedings of the International Conference on Machine Learning, 2023

2022

Learning General World Models in a Handful of Reward-Free Deployments.

Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen Roberts, Tim Rocktäschel, Edward Grefenstette

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Stabilizing Off-Policy Deep Reinforcement Learning from Pixels.

Edoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan

Proceedings of the International Conference on Machine Learning, 2022

Revisiting Design Choices in Offline Model Based Reinforcement Learning.

Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts

Proceedings of the Tenth International Conference on Learning Representations, 2022

Bayesian Generational Population-Based Training.

Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne

Proceedings of the International Conference on Automated Machine Learning, 2022

Same State, Different Task: Continual Reinforcement Learning without Interference.

Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Active Inference: Demystified and Compared.

Noor Sajid, Philip J. Ball, Thomas Parr, Karl J. Friston

Neural Comput., 2021

Revisiting Design Choices in Model-Based Offline Reinforcement Learning.

Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts

CoRR, 2021

OffCon³: What is state of the art anyway?

Philip J. Ball, Stephen J. Roberts

CoRR, 2021

Towards tractable optimism in model-based reinforcement learning.

Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment.

Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

A Study on Efficiency in Continual Learning Inspired by Human Learning.

Philip J. Ball, Yingzhen Li, Angus Lamb, Cheng Zhang

CoRR, 2020

On Optimism in Model-Based Reinforcement Learning.

Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts

CoRR, 2020

Ready Policy One: World Building Through Active Learning.

Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen J. Roberts

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Demystifying active inference.

Noor Sajid, Philip J. Ball, Karl J. Friston

CoRR, 2019

The Sensitivity of Counterfactual Fairness to Unmeasured Confounding.

Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019