Michael A. Osborne

162 papers A* 32A 20B 2C 1Journal 95Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Recurrent Structural Policy Gradient for Partially Observable Mean Field Games. CoRR Clarisse Wibault, Johannes Forkel, Sebastian Towers, Tiphaine Wibault, Juan Agustin Duque, George Whittle, Andreas Schaab, Yucheng Yang, Chiyuan Wang, Michael A. Osborne, Benjamin Moll, Jakob N. Foerster
2025	J	`jnl`	A Physics-Inspired Optimizer: Velocity Regularized Adam. CoRR Pranav Vaidhyanathan, Lucas Schorling, Natalia Ares, Michael A. Osborne
2025	J	`jnl`	Bayesian Optimization for Building Social-Influence-Free Consensus. CoRR Masaki Adachi, Siu Lun Chau, Wenjie Xu, Anurag Singh, Michael A. Osborne, Krikamol Muandet
2025	J	`jnl`	Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation. CoRR George Whittle, Juliusz Ziomek, Jacob Rawling, Michael A. Osborne
2025	—	`conf`	Fixing the Pitfalls of Probabilistic Time-Series Forecasting Evaluation by Kernel Quadrature. ProbNum Masaki Adachi, Masahiro Fujisawa, Michael A. Osborne
2025	J	`jnl`	Fixing the Pitfalls of Probabilistic Time-Series Forecasting Evaluation by Kernel Quadrature. CoRR Masaki Adachi, Masahiro Fujisawa, Michael A. Osborne
2025	J	`jnl`	Just One Layer Norm Guarantees Stable Extrapolation. CoRR Juliusz Ziomek, George Whittle, Michael A. Osborne
2025	A	`conf`	Learning to Forget: Bayesian Time Series Forecasting using Recurrent Sparse Spectrum Signature Gaussian Processes. AISTATS Csaba Tóth, Masaki Adachi, Michael A. Osborne, Harald Oberhauser
2025	J	`jnl`	Meta-learning characteristics and dynamics of quantum systems. CoRR Lucas Schorling, Pranav Vaidhyanathan, Jonas Schuff, Miguel J. Carballido, Dominik M. Zumbühl, Gerard Milburn, Florian Marquardt, Jakob N. Foerster, Michael A. Osborne, Natalia Ares
2025	—	`conf`	Natural Evolutionary Search meets Probabilistic Numerics. ProbNum Pierre Osselin, Masaki Adachi, Xiaowen Dong, Michael A. Osborne
2025	J	`jnl`	Natural Evolutionary Search meets Probabilistic Numerics. CoRR Pierre Osselin, Masaki Adachi, Xiaowen Dong, Michael A. Osborne
2025	J	`jnl`	PAC Apprenticeship Learning with Bayesian Active Inverse Reinforcement Learning. CoRR Ondrej Bajgar, Dewi S. W. Gould, Jonathon Liu, Alessandro Abate, Konstantinos Gatsis, Michael A. Osborne
2025	J	`jnl`	Position: Ensuring mutual privacy is necessary for effective external evaluation of proprietary AI systems. CoRR Ben Bucknall, Robert F. Trager, Michael A. Osborne
2025	J	`jnl`	SOReL and TOReL: Two Methods for Fully Offline Reinforcement Learning. CoRR Mattie Fellows, Clarisse Wibault, Uljad Berdica, Johannes Forkel, Michael A. Osborne, Jakob N. Foerster
2025	J	`jnl`	Scalable Valuation of Human Feedback through Provably Robust Model Alignment. CoRR Masahiro Fujisawa, Masaki Adachi, Michael A. Osborne
2025	A	`conf`	Time-varying Gaussian Process Bandits with Unknown Prior. AISTATS Juliusz Ziomek, Masaki Adachi, Michael A. Osborne
2024	J	`jnl`	A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting. CoRR Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Saad Hamid, Harald Oberhauser, Michael A. Osborne
2024	A	`conf`	Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. AISTATS Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne
2024	A*	`conf`	Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal. NeurIPS Juliusz Ziomek, Masaki Adachi, Michael A. Osborne
2024	J	`jnl`	Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal. CoRR Juliusz Ziomek, Masaki Adachi, Michael A. Osborne
2024	J	`jnl`	Beyond Lengthscales: No-regret Bayesian Optimisation With Unknown Hyperparameters Of Any Type. CoRR Juliusz Ziomek, Masaki Adachi, Michael A. Osborne
2024	J	`jnl`	Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation. CoRR Lennart Heim, Timothy Fist, Janet Egan, Sihao Huang, Stephen A. Zekany, Robert Trager, Michael A. Osborne, Noa Zilberman
2024	J	`jnl`	Learning to Forget: Bayesian Time Series Forecasting using Recurrent Sparse Spectrum Signature Gaussian Processes. CoRR Csaba Tóth, Masaki Adachi, Michael A. Osborne, Harald Oberhauser
2024	A	`conf`	Looping in the Human: Collaborative and Explainable Bayesian Optimization. AISTATS Masaki Adachi, Brady Planden, David A. Howey, Michael A. Osborne, Sebastian Orbell, Natalia Ares, Krikamol Muandet, Siu Lun Chau
2024	J	`jnl`	Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. 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
2024	A*	`conf`	Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. 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
2024	J	`jnl`	Principled Bayesian Optimisation in Collaboration with Human Experts. CoRR Wenjie Xu, Masaki Adachi, Colin N. Jones, Michael A. Osborne
2024	A*	`conf`	Principled Bayesian Optimization in Collaboration with Human Experts. NeurIPS Wenjie Xu, Masaki Adachi, Colin N. Jones, Michael A. Osborne
2024	A	`conf`	Walking the Values in Bayesian Inverse Reinforcement Learning. UAI Ondrej Bajgar, Alessandro Abate, Konstantinos Gatsis, Michael A. Osborne
2024	J	`jnl`	Walking the Values in Bayesian Inverse Reinforcement Learning. CoRR Ondrej Bajgar, Alessandro Abate, Konstantinos Gatsis, Michael A. Osborne
2023	A*	`conf`	Bayesian Optimisation of Functions on Graphs. NeurIPS Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong
2023	J	`jnl`	Bayesian Optimisation of Functions on Graphs. CoRR Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong
2023	J	`jnl`	Bayesian Quadrature for Neural Ensemble Search. CoRR Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne
2023	J	`jnl`	Bayesian Quadrature for Neural Ensemble Search. Trans. Mach. Learn. Res. Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne
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	J	`jnl`	Domain-Agnostic Batch Bayesian Optimization with Diverse Constraints via Bayesian Quadrature. CoRR Masaki Adachi, Satoshi Hayakawa, Xingchen Wan, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
2023	J	`jnl`	Looping in the Human: Collaborative and Explainable Bayesian Optimization. CoRR Masaki Adachi, Brady Planden, David A. Howey, Krikamol Muandet, Michael A. Osborne, Siu Lun Chau
2023	J	`jnl`	SOBER: Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints. CoRR Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
2022	J	`jnl`	Advanced Artificial Agents Intervene in the Provision of Reward. AI Mag. Michael K. Cohen, Marcus Hutter, Michael A. Osborne
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`	Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian Quadrature. CoRR Masaki Adachi, Yannick Kuhn, Birger Horstmann, Michael A. Osborne, David A. Howey
2022	A*	`conf`	Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. NeurIPS Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy
2022	J	`jnl`	Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. CoRR Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy
2022	A*	`conf`	Bezier Gaussian Processes for Tall and Wide Data. NeurIPS Martin Jørgensen, Michael A. Osborne
2022	J	`jnl`	Bézier Gaussian Processes for Tall and Wide Data. CoRR Martin Jørgensen, 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`	Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. NeurIPS Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
2022	J	`jnl`	Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. CoRR Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
2022	A*	`conf`	Log-Linear-Time Gaussian Processes Using Binary Tree Kernels. NeurIPS Michael K. Cohen, Samuel Daulton, Michael A. Osborne
2022	J	`jnl`	Log-Linear-Time Gaussian Processes Using Binary Tree Kernels. CoRR Michael K. Cohen, Samuel Daulton, Michael A. Osborne
2022	A	`conf`	Marginalising over Stationary Kernels with Bayesian Quadrature. AISTATS Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts
2022	J	`jnl`	Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts
2022	J	`jnl`	On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations. CoRR Tim G. J. Rudner, Cong Lu, Michael A. Osborne, Yarin Gal, Yee Whye Teh
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`	Robust Multi-Objective Bayesian Optimization Under Input Noise. ICML Samuel Daulton, Sait Cakmak, Maximilian Balandat, Michael A. Osborne, Enlu Zhou, Eytan Bakshy
2022	J	`jnl`	Robust Multi-Objective Bayesian Optimization Under Input Noise. CoRR Samuel Daulton, Sait Cakmak, Maximilian Balandat, Michael A. Osborne, Enlu Zhou, Eytan Bakshy
2022	J	`jnl`	Universal Approximation of Functions on Sets. J. Mach. Learn. Res. Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Michael A. Osborne, Ingmar Posner
2021	J	`jnl`	Adversarial Attacks on Graph Classification via Bayesian Optimisation. CoRR Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong
2021	A*	`conf`	Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. NeurIPS Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong
2021	J	`jnl`	Bridging the reality gap in quantum devices with physics-aware machine learning. CoRR David L. Craig, H. Moon, Federico Fedele, Dominic T. Lennon, Barnaby van Straaten, Florian Vigneau, Leon C. Camenzind, Dominik M. Zumbühl, G. Andrew D. Briggs, Michael A. Osborne, Dino Sejdinovic, Natalia Ares
2021	J	`jnl`	Cross-architecture Tuning of Silicon and SiGe-based Quantum Devices Using Machine Learning. CoRR Brandon Severin, Dominic T. Lennon, Leon C. Camenzind, Florian Vigneau, Federico Fedele, D. Jirovec, A. Ballabio, Daniel Chrastina, Giovanni Isella, M. de Kruijf, Miguel J. Carballido, Simon Svab, Andreas V. Kuhlmann, F. R. Braakman, Simon Geyer, F. N. M. Froning, H. Moon, Michael A. Osborne, Dino Sejdinovic, G. Katsaros, Dominik M. Zumbühl, G. Andrew D. Briggs, Natalia Ares
2021	J	`jnl`	Gaussian Process Sampling and Optimization with Approximate Upper and Lower Bounds. CoRR Vu Nguyen, Marc Peter Deisenroth, Michael A. Osborne
2021	A*	`conf`	Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels. ICLR Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne
2021	J	`jnl`	Marginalising over Stationary Kernels with Bayesian Quadrature. CoRR Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts
2021	A*	`conf`	On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations. NeurIPS Tim G. J. Rudner, Cong Lu, Michael A. Osborne, Yarin Gal, Yee Whye Teh
2021	A*	`conf`	Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search. ICML Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne
2021	J	`jnl`	Personalized brain stimulation for effective neurointervention across participants. PLoS Comput. Biol. Nienke E. R. van Bueren, Thomas L. Reed, Vu Nguyen, James G. Sheffield, Sanne H. G. van der Ven, Michael A. Osborne, Evelyn H. Kroesbergen, Roi Cohen Kadosh
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	A*	`conf`	Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces. ICML Xingchen Wan, Vu Nguyen, Huong Ha, Bin Xin Ru, Cong Lu, Michael A. Osborne
2021	J	`jnl`	Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces. CoRR Xingchen Wan, Vu Nguyen, Huong Ha, Bin Xin Ru, Cong Lu, Michael A. Osborne
2021	J	`jnl`	Universal Approximation of Functions on Sets. CoRR Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Michael A. Osborne, Ingmar Posner
2020	A*	`conf`	Bayesian Optimisation over Multiple Continuous and Categorical Inputs. ICML Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts
2020	A*	`conf`	Bayesian Optimization for Iterative Learning. NeurIPS Vu Nguyen, Sebastian Schulze, Michael A. Osborne
2020	J	`jnl`	Deep Reinforcement Learning for Efficient Measurement of Quantum Devices. CoRR V. Nguyen, S. B. Orbell, Dominic T. Lennon, Hyungil Moon, Florian Vigneau, Leon C. Camenzind, Liuqi Yu, Dominik M. Zumbühl, G. Andrew D. Briggs, Michael A. Osborne, Dino Sejdinovic, Natalia Ares
2020	J	`jnl`	Distributionally Ambiguous Optimization for Batch Bayesian Optimization. J. Mach. Learn. Res. Nikitas Rontsis, Michael A. Osborne, Paul J. Goulart
2020	A*	`conf`	Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective. NeurIPS Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood
2020	J	`jnl`	Gaussian Process Bandit Optimization of theThermodynamic Variational Objective. CoRR Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood
2020	A*	`conf`	Knowing The What But Not The Where in Bayesian Optimization. ICML Vu Nguyen, Michael A. Osborne
2020	J	`jnl`	Machine learning enables completely automatic tuning of a quantum device faster than human experts. CoRR Hyungil Moon, Dominic T. Lennon, James Kirkpatrick, Nina M. van Esbroeck, Leon C. Camenzind, Liuqi Yu, Florian Vigneau, Dominik M. Zumbühl, G. Andrew D. Briggs, Michael A. Osborne, Dino Sejdinovic, Edward A. Laird, Natalia Ares
2020	J	`jnl`	Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel. CoRR Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne
2020	A*	`conf`	ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer
2020	J	`jnl`	Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search. CoRR Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne
2020	A	`conf`	Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning. AISTATS Sebastian Farquhar, Michael A. Osborne, Yarin Gal
2020	J	`jnl`	Robust Reinforcement Learning with Bayesian Optimisation and Quadrature. J. Mach. Learn. Res. Supratik Paul, Konstantinos I. Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson
2019	J	`jnl`	A General Framework for Fair Regression. Entropy Jack K. Fitzsimons, AbdulRahman Al Ali, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	A Maximum Entropy approach to Massive Graph Spectra. CoRR Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs. CoRR Gabriele Abbati, Philippe Wenk, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf
2019	A*	`conf`	AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. ICML Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer
2019	J	`jnl`	Adaptive Configuration Oracle for Online Portfolio Selection Methods. CoRR Favour M. Nyikosa, Michael A. Osborne, Stephen J. Roberts
2019	A*	`conf`	Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. ICML Ahsan S. Alvi, Bin Xin Ru, Jan-Peter Calliess, Stephen J. Roberts, Michael A. Osborne
2019	J	`jnl`	Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. CoRR Ahsan S. Alvi, Bin Xin Ru, Jan Calliess, Stephen J. Roberts, Michael A. Osborne
2019	A*	`conf`	Automated Model Selection with Bayesian Quadrature. ICML Henry Chai, Jean-Francois Ton, Michael A. Osborne, Roman Garnett
2019	J	`jnl`	Automated Model Selection with Bayesian Quadrature. CoRR Henry Chai, Jean-Francois Ton, Roman Garnett, Michael A. Osborne
2019	J	`jnl`	Bayesian Optimisation over Multiple Continuous and Categorical Inputs. CoRR Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	Bayesian Optimization for Iterative Learning. CoRR Vu Nguyen, Sebastian Schulze, Michael A. Osborne
2019	A*	`conf`	Fingerprint Policy Optimisation for Robust Reinforcement Learning. ICML Supratik Paul, Michael A. Osborne, Shimon Whiteson
2019	J	`jnl`	Gaussian Process Regression for In Situ Capacity Estimation of Lithium-Ion Batteries. IEEE Trans. Ind. Informatics Robert R. Richardson, Christoph R. Birkl, Michael A. Osborne, David A. Howey
2019	C	`conf`	Inferring Work Task Automatability from AI Expert Evidence. AIES Paul Duckworth, Logan Graham, Michael A. Osborne
2019	J	`jnl`	Knowing The What But Not The Where in Bayesian Optimization. CoRR Vu Nguyen, Michael A. Osborne
2019	J	`jnl`	MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. CoRR Philippe Wenk, Gabriele Abbati, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf
2019	A*	`conf`	On the Limitations of Representing Functions on Sets. ICML Edward Wagstaff, Fabian Fuchs, Martin Engelcke, Ingmar Posner, Michael A. Osborne
2019	J	`jnl`	On the Limitations of Representing Functions on Sets. CoRR Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Ingmar Posner, Michael A. Osborne
2019	J	`jnl`	Radial Bayesian Neural Networks: Robust Variational Inference In Big Models. CoRR Sebastian Farquhar, Michael A. Osborne, Yarin Gal
2018	A	`conf`	AdaGeo: Adaptive Geometric Learning for Optimization and Sampling. AISTATS Gabriele Abbati, Alessandra Tosi, Michael A. Osborne, Seth R. Flaxman
2018	A*	`conf`	Alternating Optimisation and Quadrature for Robust Control. AAAI Supratik Paul, Konstantinos I. Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson
2018	J	`jnl`	Batch Selection for Parallelisation of Bayesian Quadrature. CoRR Edward Wagstaff, Saad Hamid, Michael A. Osborne
2018	J	`jnl`	Contextual Policy Optimisation. CoRR Supratik Paul, Michael A. Osborne, Shimon Whiteson
2018	J	`jnl`	Efficiently measuring a quantum device using machine learning. CoRR Dominic T. Lennon, Hyungil Moon, Leon C. Camenzind, Liuqi Yu, Dominik M. Zumbühl, G. Andrew D. Briggs, Michael A. Osborne, Edward A. Laird, Natalia Ares
2018	J	`jnl`	Entropic Spectral Learning in Large Scale Networks. CoRR Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2018	J	`jnl`	Equality Constrained Decision Trees: For the Algorithmic Enforcement of Group Fairness. CoRR Jack K. Fitzsimons, AbdulRahman Al Ali, Michael A. Osborne, Stephen J. Roberts
2018	A*	`conf`	Fast Information-theoretic Bayesian Optimisation. ICML Bin Xin Ru, Mark McLeod, Diego Granziol, Michael A. Osborne
2018	A	`conf`	Improved Stochastic Trace Estimation using Mutually Unbiased Bases. UAI Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph Francis Fitzsimons
2018	J	`jnl`	Intersectionality: Multiple Group Fairness in Expectation Constraints. CoRR Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts
2018	A*	`conf`	Optimization, Fast and Slow: Optimally Switching between Local and Bayesian Optimization. ICML Mark McLeod, Stephen J. Roberts, Michael A. Osborne
2018	J	`jnl`	Optimization, fast and slow: optimally switching between local and Bayesian optimization. CoRR Mark McLeod, Michael A. Osborne, Stephen J. Roberts
2018	J	`jnl`	Quantum algorithms for training Gaussian Processes. CoRR Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons
2018	J	`jnl`	Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?". CoRR François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic
2018	J	`jnl`	Spatial Field Reconstruction and Sensor Selection in Heterogeneous Sensor Networks With Stochastic Energy Harvesting. IEEE Trans. Signal Process. Pengfei Zhang, Ido Nevat, Gareth W. Peters, François Septier, Michael A. Osborne
2018	J	`jnl`	VBALD - Variational Bayesian Approximation of Log Determinants. CoRR Diego Granziol, Edward Wagstaff, Bin Xin Ru, Michael A. Osborne, Stephen J. Roberts
2017	J	`jnl`	A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes. CoRR Syed Ali Asad Rizvi, Stephen J. Roberts, Michael A. Osborne, Favour Nyikosa
2017	B	`conf`	Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer's Disease. AIME Wolfgang Fruehwirt, Pengfei Zhang, Matthias Gerstgrasser, Dieter Grossegger, Reinhold Schmidt, Thomas Benke, Peter Dal-Bianco, Gerhard Ransmayr, Leonard Weydemann, Heinrich Garn, Markus Waser, Michael A. Osborne, Georg Dorffner
2017	A	`conf`	Bayesian Inference of Log Determinants. UAI Jack K. Fitzsimons, Kurt Cutajar, Maurizio Filippone, Michael A. Osborne, Stephen J. Roberts
2017	J	`jnl`	Bayesian Inference of Log Determinants. CoRR Jack K. Fitzsimons, Kurt Cutajar, Michael A. Osborne, Stephen J. Roberts, Maurizio Filippone
2017	J	`jnl`	Bayesian Optimization for Probabilistic Programs. CoRR Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank D. Wood
2017	A	`conf`	Distribution of Gaussian Process Arc Lengths. AISTATS Justin Bewsher, Alessandra Tosi, Michael A. Osborne, Stephen J. Roberts
2017	—	`conf`	Entropic Trace Estimates for Log Determinants. ECML/PKDD (1) Jack K. Fitzsimons, Diego Granziol, Kurt Cutajar, Michael A. Osborne, Maurizio Filippone, Stephen J. Roberts
2017	J	`jnl`	Entropic Trace Estimates for Log Determinants. CoRR Jack K. Fitzsimons, Diego Granziol, Kurt Cutajar, Michael A. Osborne, Maurizio Filippone, Stephen J. Roberts
2017	—	`conf`	Identifying Sources of Discrimination Risk in the Life Cycle of Machine Intelligence Applications under New European Union Regulations. AAAI Spring Symposia Syed Ali Asad Rizvi, Elmarie van Heerden, Arnold Salas, Favour Nyikosa, Stephen J. Roberts, Michael A. Osborne, Elmer Rodriguez
2016	J	`jnl`	Alternating Optimisation and Quadrature for Robust Reinforcement Learning. CoRR Supratik Paul, Kamil Ciosek, Michael A. Osborne, Shimon Whiteson
2016	—	`conf`	Bayesian Optimization for Probabilistic Programs. NIPS Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank D. Wood
2016	A	`conf`	GLASSES: Relieving The Myopia Of Bayesian Optimisation. AISTATS Javier González, Michael A. Osborne, Neil D. Lawrence
2016	J	`jnl`	Improved stochastic trace estimation using mutually unbiased bases. CoRR Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons
2016	A	`conf`	Latent Point Process Allocation. AISTATS Chris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts, Tom Nickson
2016	A*	`conf`	Preconditioning Kernel Matrices. ICML Kurt Cutajar, Michael A. Osborne, John P. Cunningham, Maurizio Filippone
2015	—	`conf`	Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees. NIPS François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne
2015	J	`jnl`	Probabilistic Integration. CoRR François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic
2015	J	`jnl`	Probabilistic Numerics and Uncertainty in Computations. CoRR Philipp Hennig, Michael A. Osborne, Mark A. Girolami
2015	A*	`conf`	Variational Inference for Gaussian Process Modulated Poisson Processes. ICML Chris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts
2014	A	`conf`	Active Learning of Linear Embeddings for Gaussian Processes. UAI Roman Garnett, Michael A. Osborne, Philipp Hennig
2014	J	`jnl`	Communication Communities in MOOCs. CoRR Nabeel Gillani, Rebecca Eynon, Michael A. Osborne, Isis Hjorth, Stephen J. Roberts
2014	A	`conf`	Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space. AAMAS Jan-Peter Calliess, Michael A. Osborne, Stephen J. Roberts
2014	J	`jnl`	Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space. CoRR Jan-Peter Calliess, Michael A. Osborne, Stephen J. Roberts
2014	A	`conf`	Efficient Bayesian Nonparametric Modelling of Structured Point Processes. UAI Tom Gunter, Chris M. Lloyd, Michael A. Osborne, Stephen J. Roberts
2014	—	`conf`	Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature. NIPS Tom Gunter, Michael A. Osborne, Roman Garnett, Philipp Hennig, Stephen J. Roberts
2013	J	`jnl`	A Kernel for Hierarchical Parameter Spaces. CoRR Frank Hutter, Michael A. Osborne
2013	J	`jnl`	Active Learning of Linear Embeddings for Gaussian Processes. CoRR Roman Garnett, Michael A. Osborne, Philipp Hennig
2013	A	`conf`	AgentSwitch: towards smart energy tariff selection. AAMAS Sarvapali D. Ramchurn, Michael A. Osborne, Oliver Parson, Talal Rahwan, Sasan Maleki, Steven Reece, Trung Dong Huynh, Muddasser Alam, Joel E. Fischer, Tom Rodden, Luc Moreau, Stephen J. Roberts
2013	A	`conf`	AgentSwitch: towards smart energy tariff selection. AAMAS Sarvapali D. Ramchurn, Michael A. Osborne, Oliver Parson, Talal Rahwan, Sasan Maleki, Steven Reece, Trung Dong Huynh, Muddasser Alam, Joel E. Fischer, Tom Rodden, Luc Moreau, Stephen J. Roberts
2013	A	`conf`	Recommending energy tariffs and load shifting based on smart household usage profiling. IUI Joel E. Fischer, Sarvapali D. Ramchurn, Michael A. Osborne, Oliver Parson, Trung Dong Huynh, Muddasser Alam, Nadia Pantidi, Stuart Moran, Khaled Bachour, Steven Reece, Enrico Costanza, Tom Rodden, Nicholas R. Jennings
2012	—	`conf`	Active Learning of Model Evidence Using Bayesian Quadrature. NIPS Michael A. Osborne, David Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani
2012	A	`conf`	Bayesian Quadrature for Ratios. AISTATS Michael A. Osborne, Roman Garnett, Stephen J. Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson
2012	—	`conf`	Can priors be trusted? Learning to anticipate roadworks. ITSC Bonolo Mathibela, Michael A. Osborne, Ingmar Posner, Paul Newman
2012	A*	`conf`	Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults. AAAI Michael A. Osborne, Roman Garnett, Kevin Swersky, Nando de Freitas
2012	J	`jnl`	Real-time information processing of environmental sensor network data using bayesian gaussian processes. ACM Trans. Sens. Networks Michael A. Osborne, Stephen J. Roberts, Alex Rogers, Nicholas R. Jennings
2010	B	`conf`	Active Data Selection for Sensor Networks with Faults and Changepoints. AINA Michael A. Osborne, Roman Garnett, Stephen J. Roberts
2010	—	`conf`	Bayesian optimization for sensor set selection. IPSN Roman Garnett, Michael A. Osborne, Stephen J. Roberts
2010	J	`jnl`	Sequential Bayesian Prediction in the Presence of Changepoints and Faults. Comput. J. Roman Garnett, Michael A. Osborne, Steven Reece, Alex Rogers, Stephen J. Roberts
2009	A*	`conf`	Sequential Bayesian prediction in the presence of changepoints. ICML Roman Garnett, Michael A. Osborne, Stephen J. Roberts
2008	—	`conf`	Towards Real-Time Information Processing of Sensor Network Data Using Computationally Efficient Multi-output Gaussian Processes. IPSN Michael A. Osborne, Stephen J. Roberts, Alex Rogers, Sarvapali D. Ramchurn, Nicholas R. Jennings