Philip J. Ball

30 papers A* 8A 2Journal 19Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. RLJ Rafael Rafailov, Kyle Beltran Hatch, Anikait Singh, Aviral Kumar, Laura Smith, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Sergey Levine, Chelsea Finn
2024	J	`jnl`	D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. CoRR Rafael Rafailov, Kyle Hatch, Anikait Singh, Laura Smith, Aviral Kumar, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Chelsea Finn, Sergey Levine
2023	J	`jnl`	Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. Trans. Mach. Learn. Res. Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh
2023	A*	`conf`	Efficient Online Reinforcement Learning with Offline Data. ICML Philip J. Ball, Laura Smith, Ilya Kostrikov, Sergey Levine
2023	J	`jnl`	Efficient Online Reinforcement Learning with Offline Data. CoRR Philip J. Ball, Laura Smith, Ilya Kostrikov, Sergey Levine
2023	A*	`conf`	Synthetic Experience Replay. NeurIPS Cong Lu, Philip J. Ball, Yee Whye Teh, Jack Parker-Holder
2023	J	`jnl`	Synthetic Experience Replay. CoRR Cong Lu, Philip J. Ball, Jack Parker-Holder
2022	—	`conf`	Bayesian Generational Population-Based Training. AutoML Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne
2022	J	`jnl`	Bayesian Generational Population-Based Training. CoRR Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne
2022	J	`jnl`	Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. CoRR Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh
2022	A*	`conf`	Learning General World Models in a Handful of Reward-Free Deployments. NeurIPS Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen Roberts, Tim Rocktäschel, Edward Grefenstette
2022	J	`jnl`	Learning General World Models in a Handful of Reward-Free Deployments. CoRR Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen J. Roberts, Tim Rocktäschel, Edward Grefenstette
2022	A*	`conf`	Revisiting Design Choices in Offline Model Based Reinforcement Learning. ICLR Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts
2022	A*	`conf`	Same State, Different Task: Continual Reinforcement Learning without Interference. AAAI Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
2022	A*	`conf`	Stabilizing Off-Policy Deep Reinforcement Learning from Pixels. ICML Edoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan
2022	J	`jnl`	Stabilizing Off-Policy Deep Reinforcement Learning from Pixels. CoRR Edoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan
2021	J	`jnl`	Active Inference: Demystified and Compared. Neural Comput. Noor Sajid, Philip J. Ball, Thomas Parr, Karl J. Friston
2021	A*	`conf`	Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. ICML Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts
2021	J	`jnl`	Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. CoRR Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts
2021	J	`jnl`	OffCon CoRR Philip J. Ball, Stephen J. Roberts
2021	J	`jnl`	Revisiting Design Choices in Model-Based Offline Reinforcement Learning. CoRR Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts
2021	J	`jnl`	Same State, Different Task: Continual Reinforcement Learning without Interference. CoRR Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
2021	A	`conf`	Towards tractable optimism in model-based reinforcement learning. UAI Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts
2020	J	`jnl`	A Study on Efficiency in Continual Learning Inspired by Human Learning. CoRR Philip J. Ball, Yingzhen Li, Angus Lamb, Cheng Zhang
2020	J	`jnl`	On Optimism in Model-Based Reinforcement Learning. CoRR Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts
2020	A*	`conf`	Ready Policy One: World Building Through Active Learning. ICML Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen J. Roberts
2020	J	`jnl`	Ready Policy One: World Building Through Active Learning. CoRR Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts
2019	J	`jnl`	Demystifying active inference. CoRR Noor Sajid, Philip J. Ball, Karl J. Friston
2019	A	`conf`	The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. UAI Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva
2019	J	`jnl`	The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. CoRR Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva