Ian Osband - RankMe

59 papers A* 12A 3Journal 39Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Delightful Distributed Policy Gradient. CoRR Ian Osband
2026	J	`jnl`	Delightful Policy Gradient. CoRR Ian Osband
2026	J	`jnl`	Does This Gradient Spark Joy? CoRR Ian Osband
2023	A	`conf`	Approximate Thompson Sampling via Epistemic Neural Networks. UAI Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
2023	J	`jnl`	Approximate Thompson Sampling via Epistemic Neural Networks. CoRR Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
2023	J	`jnl`	Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping. Trans. Mach. Learn. Res. Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy
2023	A*	`conf`	Epistemic Neural Networks. NeurIPS Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
2023	J	`jnl`	Reinforcement Learning, Bit by Bit. Found. Trends Mach. Learn. Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen
2022	J	`jnl`	Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping. CoRR Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy
2022	J	`jnl`	Evaluating High-Order Predictive Distributions in Deep Learning. CoRR Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy
2022	A	`conf`	Evaluating high-order predictive distributions in deep learning. UAI Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy
2022	J	`jnl`	Fine-Tuning Language Models via Epistemic Neural Networks. CoRR Ian Osband, Seyed Mohammad Asghari, Benjamin Van Roy, Nat McAleese, John Aslanides, Geoffrey Irving
2022	J	`jnl`	Robustness of Epinets against Distributional Shifts. CoRR Xiuyuan Lu, Ian Osband, Seyed Mohammad Asghari, Sven Gowal, Vikranth Dwaracherla, Zheng Wen, Benjamin Van Roy
2022	A*	`conf`	The Neural Testbed: Evaluating Joint Predictions. NeurIPS Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy
2021	J	`jnl`	Epistemic Neural Networks. CoRR Ian Osband, Zheng Wen, Mohammad Asghari, Morteza Ibrahimi, Xiyuan Lu, Benjamin Van Roy
2021	J	`jnl`	Evaluating Predictive Distributions: Does Bayesian Deep Learning Work? CoRR Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy
2021	J	`jnl`	Evaluating Probabilistic Inference in Deep Learning: Beyond Marginal Predictions. CoRR Xiuyuan Lu, Ian Osband, Benjamin Van Roy, Zheng Wen
2021	A	`conf`	Matrix games with bandit feedback. UAI Brendan O'Donoghue, Tor Lattimore, Ian Osband
2021	J	`jnl`	Reinforcement Learning, Bit by Bit. CoRR Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen
2020	A*	`conf`	Behaviour Suite for Reinforcement Learning. ICLR Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvári, Satinder Singh, Benjamin Van Roy, Richard S. Sutton, David Silver, Hado van Hasselt
2020	A*	`conf`	Hypermodels for Exploration. ICLR Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy
2020	J	`jnl`	Hypermodels for Exploration. CoRR Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy
2020	A*	`conf`	Making Sense of Reinforcement Learning and Probabilistic Inference. ICLR Brendan O'Donoghue, Ian Osband, Catalin Ionescu
2020	J	`jnl`	Making Sense of Reinforcement Learning and Probabilistic Inference. CoRR Brendan O'Donoghue, Ian Osband, Catalin Ionescu
2020	J	`jnl`	Stochastic matrix games with bandit feedback. CoRR Brendan O'Donoghue, Tor Lattimore, Ian Osband
2019	J	`jnl`	Behaviour Suite for Reinforcement Learning. CoRR Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvári, Satinder Singh, Benjamin Van Roy, Richard S. Sutton, David Silver, Hado van Hasselt
2019	J	`jnl`	Deep Exploration via Randomized Value Functions. J. Mach. Learn. Res. Ian Osband, Benjamin Van Roy, Daniel J. Russo, Zheng Wen
2019	J	`jnl`	Meta-learning of Sequential Strategies. CoRR Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew M. Botvinick, Shane Legg
2018	J	`jnl`	A Tutorial on Thompson Sampling. Found. Trends Mach. Learn. Daniel Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband, Zheng Wen
2018	A*	`conf`	Deep Q-learning From Demonstrations. AAAI Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys
2018	—	`conf`	Noisy Networks For Exploration. ICLR (Poster) Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Matteo Hessel, Ian Osband, Alex Graves, Volodymyr Mnih, Rémi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg
2018	A*	`conf`	Randomized Prior Functions for Deep Reinforcement Learning. NeurIPS Ian Osband, John Aslanides, Albin Cassirer
2018	J	`jnl`	Randomized Prior Functions for Deep Reinforcement Learning. CoRR Ian Osband, John Aslanides, Albin Cassirer
2018	A*	`conf`	Scalable Coordinated Exploration in Concurrent Reinforcement Learning. NeurIPS Maria Dimakopoulou, Ian Osband, Benjamin Van Roy
2018	J	`jnl`	Scalable Coordinated Exploration in Concurrent Reinforcement Learning. CoRR Maria Dimakopoulou, Ian Osband, Benjamin Van Roy
2018	A*	`conf`	The Uncertainty Bellman Equation and Exploration. ICML Brendan O'Donoghue, Ian Osband, Rémi Munos, Volodymyr Mnih
2017	J	`jnl`	A Tutorial on Thompson Sampling. CoRR Daniel Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband
2017	J	`jnl`	Deep Exploration via Randomized Value Functions. CoRR Ian Osband, Daniel Russo, Zheng Wen, Benjamin Van Roy
2017	J	`jnl`	Gaussian-Dirichlet Posterior Dominance in Sequential Learning. CoRR Ian Osband, Benjamin Van Roy
2017	J	`jnl`	Learning from Demonstrations for Real World Reinforcement Learning. CoRR Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys
2017	A*	`conf`	Minimax Regret Bounds for Reinforcement Learning. ICML Mohammad Gheshlaghi Azar, Ian Osband, Rémi Munos
2017	J	`jnl`	Minimax Regret Bounds for Reinforcement Learning. CoRR Mohammad Gheshlaghi Azar, Ian Osband, Rémi Munos
2017	J	`jnl`	Noisy Networks for Exploration. CoRR Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Ian Osband, Alex Graves, Vlad Mnih, Rémi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg
2017	J	`jnl`	On Optimistic versus Randomized Exploration in Reinforcement Learning. CoRR Ian Osband, Benjamin Van Roy
2017	J	`jnl`	The Uncertainty Bellman Equation and Exploration. CoRR Brendan O'Donoghue, Ian Osband, Rémi Munos, Volodymyr Mnih
2017	A*	`conf`	Why is Posterior Sampling Better than Optimism for Reinforcement Learning? ICML Ian Osband, Benjamin Van Roy
2016	—	`conf`	Deep Exploration via Bootstrapped DQN. NIPS Ian Osband, Charles Blundell, Alexander Pritzel, Benjamin Van Roy
2016	J	`jnl`	Deep Exploration via Bootstrapped DQN. CoRR Ian Osband, Charles Blundell, Alexander Pritzel, Benjamin Van Roy
2016	A*	`conf`	Generalization and Exploration via Randomized Value Functions. ICML Ian Osband, Benjamin Van Roy, Zheng Wen
2016	J	`jnl`	On Lower Bounds for Regret in Reinforcement Learning. CoRR Ian Osband, Benjamin Van Roy
2016	J	`jnl`	Posterior Sampling for Reinforcement Learning Without Episodes. CoRR Ian Osband, Benjamin Van Roy
2016	J	`jnl`	Why is Posterior Sampling Better than Optimism for Reinforcement Learning. CoRR Ian Osband, Benjamin Van Roy
2015	J	`jnl`	Bootstrapped Thompson Sampling and Deep Exploration. CoRR Ian Osband, Benjamin Van Roy
2014	—	`conf`	Model-based Reinforcement Learning and the Eluder Dimension. NIPS Ian Osband, Benjamin Van Roy
2014	J	`jnl`	Model-based Reinforcement Learning and the Eluder Dimension. CoRR Ian Osband, Benjamin Van Roy
2014	J	`jnl`	Near-optimal Regret Bounds for Reinforcement Learning in Factored MDPs. CoRR Ian Osband, Benjamin Van Roy
2014	—	`conf`	Near-optimal Reinforcement Learning in Factored MDPs. NIPS Ian Osband, Benjamin Van Roy
2013	—	`conf`	(More) Efficient Reinforcement Learning via Posterior Sampling. NIPS Ian Osband, Daniel Russo, Benjamin Van Roy
2013	J	`jnl`	(More) Efficient Reinforcement Learning via Posterior Sampling. CoRR Ian Osband, Daniel Russo, Benjamin Van Roy