Osborne, Michael

12 publications

UAI 2024 Walking the Values in Bayesian Inverse Reinforcement Learning Ondrej Bajgar, Alessandro Abate, Konstantinos Gatsis, Michael Osborne

AutoML 2022 Bayesian Generational Population-Based Training Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael Osborne

ICLRW 2022 Bayesian Generational Population-Based Training Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael Osborne

ICLR 2022 Revisiting Design Choices in Offline Model Based Reinforcement Learning Cong Lu, Philip Ball, Jack Parker-Holder, Michael Osborne, Stephen J. Roberts

ICMLW 2021 Attacking Graph Classification via Bayesian Optimisation Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael Osborne, Xiaowen Dong

ICLR 2021 Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels Binxin Ru, Xingchen Wan, Xiaowen Dong, Michael Osborne

NeurIPS 2020 Bayesian Optimization for Iterative Learning Vu Nguyen, Sebastian Schulze, Michael Osborne

NeurIPS 2020 Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael Osborne, Frank Wood

ICML 2016 Preconditioning Kernel Matrices Kurt Cutajar, Michael Osborne, John Cunningham, Maurizio Filippone

ICML 2015 Variational Inference for Gaussian Process Modulated Poisson Processes Chris Lloyd, Tom Gunter, Michael Osborne, Stephen Roberts

NeurIPS 2012 Active Learning of Model Evidence Using Bayesian Quadrature Michael Osborne, Roman Garnett, Zoubin Ghahramani, David K. Duvenaud, Stephen J. Roberts, Carl E. Rasmussen

AISTATS 2012 Bayesian Quadrature for Ratios Michael Osborne, Roman Garnett, Stephen Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson