Osborne, Michael A.

53 publications

NeurIPS 2025 Just One Layer Norm Guarantees Stable Extrapolation Juliusz Ziomek, George Whittle, Michael A Osborne

AISTATS 2025 Learning to Forget: Bayesian Time Series Forecasting Using Recurrent Sparse Spectrum Signature Gaussian Processes Csaba Tóth, Masaki Adachi, Michael A Osborne, Harald Oberhauser

NeurIPS 2025 Scalable Valuation of Human Feedback Through Provably Robust Model Alignment Masahiro Fujisawa, Masaki Adachi, Michael A Osborne

AISTATS 2025 Time-Varying Gaussian Process Bandits with Unknown Prior Juliusz Ziomek, Masaki Adachi, Michael A Osborne

AISTATS 2024 Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne

NeurIPS 2024 Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal Juliusz Ziomek, Masaki Adachi, Michael A. Osborne

AISTATS 2024 Looping in the Human: Collaborative and Explainable Bayesian Optimization Masaki Adachi, Brady Planden, David Howey, Michael A. Osborne, Sebastian Orbell, Natalia Ares, Krikamol Muandet, Siu Lun Chau

ICML 2024 Position: Bayesian Deep Learning Is Needed in the Age of Large-Scale AI Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang

NeurIPS 2024 Principled Bayesian Optimization in Collaboration with Human Experts Wenjie Xu, Masaki Adachi, Colin N. Jones, Michael A. Osborne

NeurIPS 2023 Bayesian Optimisation of Functions on Graphs Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne, Xiaowen Dong

TMLR 2023 Bayesian Quadrature for Neural Ensemble Search Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A Osborne

TMLR 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

ICMLW 2023 SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spaces Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A Osborne

AISTATS 2022 Marginalising over Stationary Kernels with Bayesian Quadrature Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen Roberts

NeurIPS 2022 Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A Osborne, Eytan Bakshy

NeurIPS 2022 Bezier Gaussian Processes for Tall and Wide Data Martin Jørgensen, Michael A Osborne

ICMLW 2022 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

NeurIPS 2022 Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A Osborne

NeurIPS 2022 Log-Linear-Time Gaussian Processes Using Binary Tree Kernels Michael K. Cohen, Samuel Daulton, Michael A Osborne

ICML 2022 Robust Multi-Objective Bayesian Optimization Under Input Noise Samuel Daulton, Sait Cakmak, Maximilian Balandat, Michael A. Osborne, Enlu Zhou, Eytan Bakshy

JMLR 2022 Universal Approximation of Functions on Sets Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Michael A. Osborne, Ingmar Posner

NeurIPS 2021 Adversarial Attacks on Graph Classifiers via Bayesian Optimisation Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A Osborne, Xiaowen Dong

NeurIPS 2021 On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations Tim G. J. Rudner, Cong Lu, Michael A Osborne, Yarin Gal, Yee W. Teh

ICML 2021 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne

ICML 2021 Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces Xingchen Wan, Vu Nguyen, Huong Ha, Binxin Ru, Cong Lu, Michael A. Osborne

ICML 2020 Bayesian Optimisation over Multiple Continuous and Categorical Inputs Binxin Ru, Ahsan Alvi, Vu Nguyen, Michael A. Osborne, Stephen Roberts

JMLR 2020 Distributionally Ambiguous Optimization for Batch Bayesian Optimization Nikitas Rontsis, Michael A. Osborne, Paul J. Goulart

ICML 2020 Knowing the What but Not the Where in Bayesian Optimization Vu Nguyen, Michael A. Osborne

AAAI 2020 ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer

AISTATS 2020 Radial Bayesian Neural Networks: Beyond Discrete Support in Large-Scale Bayesian Deep Learning Sebastian Farquhar, Michael A. Osborne, Yarin Gal

JMLR 2020 Robust Reinforcement Learning with Bayesian Optimisation and Quadrature Supratik Paul, Konstantinos Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson

ICML 2019 AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer

ICML 2019 Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation Ahsan Alvi, Binxin Ru, Jan-Peter Calliess, Stephen Roberts, Michael A. Osborne

ICML 2019 Automated Model Selection with Bayesian Quadrature Henry Chai, Jean-Francois Ton, Michael A. Osborne, Roman Garnett

ICML 2019 Fingerprint Policy Optimisation for Robust Reinforcement Learning Supratik Paul, Michael A. Osborne, Shimon Whiteson

ICML 2019 On the Limitations of Representing Functions on Sets Edward Wagstaff, Fabian Fuchs, Martin Engelcke, Ingmar Posner, Michael A. Osborne

AISTATS 2018 AdaGeo: Adaptive Geometric Learning for Optimization and Sampling Gabriele Abbati, Alessandra Tosi, Michael A. Osborne, Seth R. Flaxman

AAAI 2018 Alternating Optimisation and Quadrature for Robust Control Supratik Paul, Konstantinos I. Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson

ICML 2018 Fast Information-Theoretic Bayesian Optimisation Binxin Ru, Michael A. Osborne, Mark Mcleod, Diego Granziol

UAI 2018 Improved Stochastic Trace Estimation Using Mutually Unbiased Bases Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph Francis Fitzsimons

ICML 2018 Optimization, Fast and Slow: Optimally Switching Between Local and Bayesian Optimization Mark McLeod, Stephen Roberts, Michael A. Osborne

UAI 2017 Bayesian Inference of Log Determinants Jack K. Fitzsimons, Kurt Cutajar, Maurizio Filippone, Michael A. Osborne, Stephen J. Roberts

AISTATS 2017 Distribution of Gaussian Process Arc Lengths Justin Bewsher, Alessandra Tosi, Michael A. Osborne, Stephen J. Roberts

ECML-PKDD 2017 Entropic Trace Estimates for Log Determinants Jack K. Fitzsimons, Diego Granziol, Kurt Cutajar, Michael A. Osborne, Maurizio Filippone, Stephen J. Roberts

NeurIPS 2016 Bayesian Optimization for Probabilistic Programs Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A Osborne, Frank Wood

AISTATS 2016 GLASSES: Relieving the Myopia of Bayesian Optimisation Javier González, Michael A. Osborne, Neil D. Lawrence

AISTATS 2016 Latent Point Process Allocation Chris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts, Tom Nickson

NeurIPS 2015 Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees François-Xavier Briol, Chris Oates, Mark Girolami, Michael A Osborne

UAI 2014 Active Learning of Linear Embeddings for Gaussian Processes Roman Garnett, Michael A. Osborne, Philipp Hennig

UAI 2014 Efficient Bayesian Nonparametric Modelling of Structured Point Processes Tom Gunter, Chris M. Lloyd, Michael A. Osborne, Stephen J. Roberts

NeurIPS 2014 Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature Tom Gunter, Michael A Osborne, Roman Garnett, Philipp Hennig, Stephen J. Roberts

AAAI 2012 Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults Michael A. Osborne, Roman Garnett, Kevin Swersky, Nando de Freitas

ICML 2009 Sequential Bayesian Prediction in the Presence of Changepoints Roman Garnett, Michael A. Osborne, Stephen J. Roberts