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Michael A. Osborne
Michael Alan Osborne
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- affiliation: University of Oxford, UK
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2020 – today
- 2024
- [c61]Masaki Adachi
, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne:
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. AISTATS 2024: 496-504 - [c60]Masaki Adachi
Looping in the Human: Collaborative and Explainable Bayesian Optimization. AISTATS 2024: 505-513 - [c59]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:
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML 2024 - [i66]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:
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR abs/2402.00809 (2024) - [i65]Juliusz Ziomek, Masaki Adachi, Michael A. Osborne:
Beyond Lengthscales: No-regret Bayesian Optimisation With Unknown Hyperparameters Of Any Type. CoRR abs/2402.01632 (2024) - [i64]Lennart Heim, Tim Fist, Janet Egan, Sihao Huang, Stephen Zekany, Robert Trager, Michael A. Osborne, Noa Zilberman:
Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation. CoRR abs/2403.08501 (2024) - [i63]Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Saad Hamid, Harald Oberhauser, Michael A. Osborne:
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting. CoRR abs/2404.12219 (2024) - [i62]Ondrej Bajgar, Alessandro Abate, Konstantinos Gatsis
Walking the Values in Bayesian Inverse Reinforcement Learning. CoRR abs/2407.10971 (2024) - 2023
- [j14]Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne:
Bayesian Quadrature for Neural Ensemble Search. Trans. Mach. Learn. Res. 2023 (2023) - [j13]Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh:
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. Trans. Mach. Learn. Res. 2023 (2023) - [c58]Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong:
Bayesian Optimisation of Functions on Graphs. NeurIPS 2023 - [i61]Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne:
SOBER: Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints. CoRR abs/2301.11832 (2023) - [i60]Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne:
Bayesian Quadrature for Neural Ensemble Search. CoRR abs/2303.08874 (2023) - [i59]Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong:
Bayesian Optimisation of Functions on Graphs. CoRR abs/2306.05304 (2023) - [i58]Masaki Adachi, Satoshi Hayakawa, Xingchen Wan, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne:
Domain-Agnostic Batch Bayesian Optimization with Diverse Constraints via Bayesian Quadrature. CoRR abs/2306.05843 (2023) - [i57]Masaki Adachi, Brady Planden, David A. Howey, Krikamol Muandet
Looping in the Human: Collaborative and Explainable Bayesian Optimization. CoRR abs/2310.17273 (2023) - 2022
- [j12]Michael K. Cohen
Advanced Artificial Agents Intervene in the Provision of Reward. AI Mag. 43(3): 282-293 (2022) - [j11]Diego Granziol
Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms 15(6): 209 (2022) - [j10]Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Michael A. Osborne, Ingmar Posner:
Universal Approximation of Functions on Sets. J. Mach. Learn. Res. 23: 151:1-151:56 (2022) - [c57]Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts:
Marginalising over Stationary Kernels with Bayesian Quadrature. AISTATS 2022: 9776-9792 - [c56]Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne:
Bayesian Generational Population-Based Training. AutoML 2022: 14/1-27 - [c55]Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts:
Revisiting Design Choices in Offline Model Based Reinforcement Learning. ICLR 2022 - [c54]Samuel Daulton, Sait Cakmak, Maximilian Balandat, Michael A. Osborne, Enlu Zhou, Eytan Bakshy:
Robust Multi-Objective Bayesian Optimization Under Input Noise. ICML 2022: 4831-4866 - [c53]Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne:
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. NeurIPS 2022 - [c52]Michael K. Cohen, Samuel Daulton, Michael A. Osborne:
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels. NeurIPS 2022 - [c51]Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy:
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. NeurIPS 2022 - [c50]Martin Jørgensen, Michael A. Osborne:
Bezier Gaussian Processes for Tall and Wide Data. NeurIPS 2022 - [i56]Samuel Daulton, Sait Cakmak, Maximilian Balandat, Michael A. Osborne, Enlu Zhou, Eytan Bakshy:
Robust Multi-Objective Bayesian Optimization Under Input Noise. CoRR abs/2202.07549 (2022) - [i55]Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne:
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. CoRR abs/2206.04734 (2022) - [i54]Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh:
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. CoRR abs/2206.04779 (2022) - [i53]Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne:
Bayesian Generational Population-Based Training. CoRR abs/2207.09405 (2022) - [i52]Martin Jørgensen, Michael A. Osborne:
Bézier Gaussian Processes for Tall and Wide Data. CoRR abs/2209.00343 (2022) - [i51]Michael K. Cohen, Samuel Daulton, Michael A. Osborne:
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels. CoRR abs/2210.01633 (2022) - [i50]Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy:
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. CoRR abs/2210.10199 (2022) - [i49]Masaki Adachi, Yannick Kuhn, Birger Horstmann, Michael A. Osborne, David A. Howey:
Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian Quadrature. CoRR abs/2210.17299 (2022) - [i48]Tim G. J. Rudner, Cong Lu, Michael A. Osborne, Yarin Gal, Yee Whye Teh:
On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations. CoRR abs/2212.13936 (2022) - 2021
- [j9]Nienke E. R. van Bueren
Personalized brain stimulation for effective neurointervention across participants. PLoS Comput. Biol. 17(9) (2021) - [c49]Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne:
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels. ICLR 2021 - [c48]Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne:
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search. ICML 2021: 8084-8095 - [c47]Xingchen Wan, Vu Nguyen, Huong Ha, Bin Xin Ru, Cong Lu, Michael A. Osborne:
Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces. ICML 2021: 10663-10674 - [c46]Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong:
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. NeurIPS 2021: 6983-6996 - [c45]Tim G. J. Rudner, Cong Lu, Michael A. Osborne, Yarin Gal, Yee Whye Teh:
On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations. NeurIPS 2021: 28376-28389 - [i47]Xingchen Wan
Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces. CoRR abs/2102.07188 (2021) - [i46]Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts:
Marginalising over Stationary Kernels with Bayesian Quadrature. CoRR abs/2106.07452 (2021) - [i45]Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Michael A. Osborne, Ingmar Posner:
Universal Approximation of Functions on Sets. CoRR abs/2107.01959 (2021) - [i44]Brandon Severin, Dominic T. Lennon, Leon C. Camenzind, Florian Vigneau, Federico Fedele, D. Jirovec, A. Ballabio, D. Chrastina, G. 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:
Cross-architecture Tuning of Silicon and SiGe-based Quantum Devices Using Machine Learning. CoRR abs/2107.12975 (2021) - [i43]Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts:
Revisiting Design Choices in Model-Based Offline Reinforcement Learning. CoRR abs/2110.04135 (2021) - [i42]Vu Nguyen, Marc Peter Deisenroth, Michael A. Osborne:
Gaussian Process Sampling and Optimization with Approximate Upper and Lower Bounds. CoRR abs/2110.12087 (2021) - [i41]Xingchen Wan
Adversarial Attacks on Graph Classification via Bayesian Optimisation. CoRR abs/2111.02842 (2021) - [i40]David L. Craig, H. Moon, Federico Fedele, Dominic T. Lennon
Bridging the reality gap in quantum devices with physics-aware machine learning. CoRR abs/2111.11285 (2021) - 2020
- [j8]Nikitas Rontsis, Michael A. Osborne, Paul J. Goulart:
Distributionally Ambiguous Optimization for Batch Bayesian Optimization. J. Mach. Learn. Res. 21: 149:1-149:26 (2020) - [j7]Supratik Paul, Konstantinos I. Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson:
Robust Reinforcement Learning with Bayesian Optimisation and Quadrature. J. Mach. Learn. Res. 21: 151:1-151:31 (2020) - [c44]Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer:
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI 2020: 6364-6371 - [c43]Sebastian Farquhar, Michael A. Osborne, Yarin Gal:
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning. AISTATS 2020: 1352-1362 - [c42]Vu Nguyen, Michael A. Osborne:
Knowing The What But Not The Where in Bayesian Optimization. ICML 2020: 7317-7326 - [c41]Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts:
Bayesian Optimisation over Multiple Continuous and Categorical Inputs. ICML 2020: 8276-8285 - [c40]Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood:
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective. NeurIPS 2020 - [c39]Vu Nguyen, Sebastian Schulze, Michael A. Osborne:
Bayesian Optimization for Iterative Learning. NeurIPS 2020 - [i39]Hyungil Moon, Dominic T. Lennon
Machine learning enables completely automatic tuning of a quantum device faster than human experts. CoRR abs/2001.02589 (2020) - [i38]Bin Xin Ru, Xingchen Wan
Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel. CoRR abs/2006.07556 (2020) - [i37]Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne:
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search. CoRR abs/2006.07593 (2020) - [i36]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:
Deep Reinforcement Learning for Efficient Measurement of Quantum Devices. CoRR abs/2009.14825 (2020) - [i35]Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood:
Gaussian Process Bandit Optimization of theThermodynamic Variational Objective. CoRR abs/2010.15750 (2020)
2010 – 2019
- 2019
- [j6]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy 21(6): 551 (2019) - [j5]Jack K. Fitzsimons, AbdulRahman Al Ali, Michael A. Osborne
A General Framework for Fair Regression. Entropy 21(8): 741 (2019) - [j4]Robert R. Richardson
Gaussian Process Regression for In Situ Capacity Estimation of Lithium-Ion Batteries. IEEE Trans. Ind. Informatics 15(1): 127-138 (2019) - [c38]Paul Duckworth, Logan Graham, Michael A. Osborne:
Inferring Work Task Automatability from AI Expert Evidence. AIES 2019: 485-491 - [c37]Gabriele Abbati, Philippe Wenk, Michael A. Osborne
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. ICML 2019: 1-10 - [c36]Ahsan S. Alvi, Bin Xin Ru, Jan-Peter Calliess, Stephen J. Roberts, Michael A. Osborne
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. ICML 2019: 253-262 - [c35]Henry Chai, Jean-Francois Ton, Michael A. Osborne
Automated Model Selection with Bayesian Quadrature. ICML 2019: 931-940 - [c34]Supratik Paul, Michael A. Osborne
Fingerprint Policy Optimisation for Robust Reinforcement Learning. ICML 2019: 5082-5091 - [c33]Edward Wagstaff, Fabian Fuchs, Martin Engelcke, Ingmar Posner, Michael A. Osborne
On the Limitations of Representing Functions on Sets. ICML 2019: 6487-6494 - [i34]Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Ingmar Posner, Michael A. Osborne:
On the Limitations of Representing Functions on Sets. CoRR abs/1901.09006 (2019) - [i33]Ahsan S. Alvi, Bin Xin Ru, Jan Calliess, Stephen J. Roberts, Michael A. Osborne:
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. CoRR abs/1901.10452 (2019) - [i32]Philippe Wenk, Gabriele Abbati, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf:
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. CoRR abs/1902.06278 (2019) - [i31]Gabriele Abbati, Philippe Wenk, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf:
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs. CoRR abs/1902.08480 (2019) - [i30]Henry Chai, Jean-Francois Ton, Roman Garnett, Michael A. Osborne:
Automated Model Selection with Bayesian Quadrature. CoRR abs/1902.09724 (2019) - [i29]Vu Nguyen, Michael A. Osborne:
Knowing The What But Not The Where in Bayesian Optimization. CoRR abs/1905.02685 (2019) - [i28]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR abs/1906.01101 (2019) - [i27]Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts:
Bayesian Optimisation over Multiple Continuous and Categorical Inputs. CoRR abs/1906.08878 (2019) - [i26]Sebastian Farquhar, Michael A. Osborne, Yarin Gal:
Radial Bayesian Neural Networks: Robust Variational Inference In Big Models. CoRR abs/1907.00865 (2019) - [i25]Favour M. Nyikosa, Michael A. Osborne, Stephen J. Roberts:
Adaptive Configuration Oracle for Online Portfolio Selection Methods. CoRR abs/1908.08258 (2019) - [i24]Vu Nguyen, Sebastian Schulze, Michael A. Osborne:
Bayesian Optimization for Iterative Learning. CoRR abs/1909.09593 (2019) - [i23]Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
A Maximum Entropy approach to Massive Graph Spectra. CoRR abs/1912.09068 (2019) - 2018
- [j3]Pengfei Zhang
Spatial Field Reconstruction and Sensor Selection in Heterogeneous Sensor Networks With Stochastic Energy Harvesting. IEEE Trans. Signal Process. 66(9): 2245-2257 (2018) - [c32]Supratik Paul, Konstantinos I. Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson:
Alternating Optimisation and Quadrature for Robust Control. AAAI 2018: 3925-3933 - [c31]Gabriele Abbati, Alessandra Tosi, Michael A. Osborne
AdaGeo: Adaptive Geometric Learning for Optimization and Sampling. AISTATS 2018: 226-234 - [c30]Mark McLeod, Stephen J. Roberts, Michael A. Osborne:
Optimization, Fast and Slow: Optimally Switching between Local and Bayesian Optimization. ICML 2018: 3440-3449 - [c29]Bin Xin Ru, Mark McLeod, Diego Granziol, Michael A. Osborne:
Fast Information-theoretic Bayesian Optimisation. ICML 2018: 4381-4389 - [c28]Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph Francis Fitzsimons:
Improved Stochastic Trace Estimation using Mutually Unbiased Bases. UAI 2018: 310-318 - [i22]Diego Granziol, Edward Wagstaff, Bin Xin Ru, Michael A. Osborne, Stephen J. Roberts:
VBALD - Variational Bayesian Approximation of Log Determinants. CoRR abs/1802.08054 (2018) - [i21]Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons:
Quantum algorithms for training Gaussian Processes. CoRR abs/1803.10520 (2018) - [i20]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
Entropic Spectral Learning in Large Scale Networks. CoRR abs/1804.06802 (2018) - [i19]Mark McLeod, Michael A. Osborne, Stephen J. Roberts:
Optimization, fast and slow: optimally switching between local and Bayesian optimization. CoRR abs/1805.08610 (2018) - [i18]Supratik Paul, Michael A. Osborne, Shimon Whiteson:
Contextual Policy Optimisation. CoRR abs/1805.10662 (2018) - [i17]Jack K. Fitzsimons, AbdulRahman Al Ali, Michael A. Osborne, Stephen J. Roberts:
Equality Constrained Decision Trees: For the Algorithmic Enforcement of Group Fairness. CoRR abs/1810.05041 (2018) - [i16]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:
Efficiently measuring a quantum device using machine learning. CoRR abs/1810.10042 (2018) - [i15]Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts:
Intersectionality: Multiple Group Fairness in Expectation Constraints. CoRR abs/1811.09960 (2018) - [i14]François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic:
Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?". CoRR abs/1811.10275 (2018) - [i13]Edward Wagstaff, Saad Hamid, Michael A. Osborne:
Batch Selection for Parallelisation of Bayesian Quadrature. CoRR abs/1812.01553 (2018) - 2017
- [c27]Syed Ali Asad Rizvi, Elmarie van Heerden, Arnold Salas, Favour Nyikosa, Stephen J. Roberts, Michael A. Osborne, Elmer Rodriguez:
Identifying Sources of Discrimination Risk in the Life Cycle of Machine Intelligence Applications under New European Union Regulations. AAAI Spring Symposia 2017 - [c26]Wolfgang Fruehwirt
Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer's Disease. AIME 2017: 65-75 - [c25]Justin Bewsher, Alessandra Tosi, Michael A. Osborne
Distribution of Gaussian Process Arc Lengths. AISTATS 2017: 1412-1420 - [c24]Jack K. Fitzsimons, Diego Granziol, Kurt Cutajar, Michael A. Osborne, Maurizio Filippone
Entropic Trace Estimates for Log Determinants. ECML/PKDD (1) 2017: 323-338 - [c23]Jack K. Fitzsimons, Kurt Cutajar, Maurizio Filippone, Michael A. Osborne, Stephen J. Roberts:
Bayesian Inference of Log Determinants. UAI 2017 - [i12]Jack K. Fitzsimons, Kurt Cutajar, Michael A. Osborne, Stephen J. Roberts, Maurizio Filippone:
Bayesian Inference of Log Determinants. CoRR abs/1704.01445 (2017) - [i11]Jack K. Fitzsimons, Diego Granziol, Kurt Cutajar, Michael A. Osborne, Maurizio Filippone, Stephen J. Roberts:
Entropic Trace Estimates for Log Determinants. CoRR abs/1704.07223 (2017) - [i10]Syed Ali Asad Rizvi, Stephen J. Roberts, Michael A. Osborne, Favour Nyikosa:
A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes. CoRR abs/1705.00891 (2017) - [i9]Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank D. Wood:
Bayesian Optimization for Probabilistic Programs. CoRR abs/1707.04314 (2017) - 2016
- [c22]Chris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts, Tom Nickson:
Latent Point Process Allocation. AISTATS 2016: 389-397 - [c21]Javier González, Michael A. Osborne, Neil D. Lawrence:
GLASSES: Relieving The Myopia Of Bayesian Optimisation. AISTATS 2016: 790-799 - [c20]Kurt Cutajar, Michael A. Osborne, John P. Cunningham, Maurizio Filippone:
Preconditioning Kernel Matrices. ICML 2016: 2529-2538 - [c19]Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank D. Wood:
Bayesian Optimization for Probabilistic Programs. NIPS 2016: 280-288 - [i8]Supratik Paul, Kamil Ciosek, Michael A. Osborne, Shimon Whiteson:
Alternating Optimisation and Quadrature for Robust Reinforcement Learning. CoRR abs/1605.07496 (2016) - [i7]Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons:
Improved stochastic trace estimation using mutually unbiased bases. CoRR abs/1608.00117 (2016) - 2015
- [c18]Chris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts:
Variational Inference for Gaussian Process Modulated Poisson Processes. ICML 2015: 1814-1822 - [c17]François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne:
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees. NIPS 2015: 1162-1170 - [i6]Philipp Hennig, Michael A. Osborne, Mark A. Girolami:
Probabilistic Numerics and Uncertainty in Computations. CoRR abs/1506.01326 (2015) - [i5]François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic:
Probabilistic Integration. CoRR abs/1512.00933 (2015) - 2014
- [c16]Jan-Peter Calliess, Michael A. Osborne, Stephen J. Roberts:
Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space. AAMAS 2014: 1109-1116 - [c15]Tom Gunter, Michael A. Osborne, Roman Garnett, Philipp Hennig, Stephen J. Roberts:
Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature. NIPS 2014: 2789-2797 - [c14]Roman Garnett, Michael A. Osborne, Philipp Hennig:
Active Learning of Linear Embeddings for Gaussian Processes. UAI 2014: 230-239 - [c13]Tom Gunter, Chris M. Lloyd, Michael A. Osborne, Stephen J. Roberts:
Efficient Bayesian Nonparametric Modelling of Structured Point Processes. UAI 2014: 310-319 - [i4]Jan-Peter Calliess, Michael A. Osborne, Stephen J. Roberts:
Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space. CoRR abs/1402.4157 (2014) - [i3]Nabeel Gillani, Rebecca Eynon, Michael A. Osborne, Isis Hjorth, Stephen J. Roberts:
Communication Communities in MOOCs. CoRR abs/1403.4640 (2014) - 2013
- [c12]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:
AgentSwitch: towards smart energy tariff selection. AAMAS 2013: 981-988 - [c11]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:
AgentSwitch: towards smart energy tariff selection. AAMAS 2013: 1401-1402 - [c10]Joel E. Fischer
Recommending energy tariffs and load shifting based on smart household usage profiling. IUI 2013: 383-394 - [i2]Frank Hutter, Michael A. Osborne:
A Kernel for Hierarchical Parameter Spaces. CoRR abs/1310.5738 (2013) - [i1]Roman Garnett, Michael A. Osborne, Philipp Hennig:
Active Learning of Linear Embeddings for Gaussian Processes. CoRR abs/1310.6740 (2013) - 2012
- [j2]Michael A. Osborne
Real-time information processing of environmental sensor network data using bayesian gaussian processes. ACM Trans. Sens. Networks 9(1): 1:1-1:32 (2012) - [c9]Jan-Peter Calliess, Michael Alan Osborne, Stephen J. Roberts:
Towards Optimization-Based Multi-Agent Collision-Avoidance Under Continuous Stochastic Dynamics. MAPF@AAAI 2012 - [c8]Michael A. Osborne, Roman Garnett, Kevin Swersky, Nando de Freitas:
Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults. AAAI 2012: 349-355 - [c7]Bonolo Mathibela, Michael A. Osborne, Ingmar Posner, Paul Newman:
Can priors be trusted? Learning to anticipate roadworks. ITSC 2012: 927-932 - [c6]Michael A. Osborne, David Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani:
Active Learning of Model Evidence Using Bayesian Quadrature. NIPS 2012: 46-54 - [c5]Michael A. Osborne, Roman Garnett, Stephen J. Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson:
Bayesian Quadrature for Ratios. AISTATS 2012: 832-840 - 2010
- [j1]Roman Garnett, Michael A. Osborne, Steven Reece, Alex Rogers, Stephen J. Roberts:
Sequential Bayesian Prediction in the Presence of Changepoints and Faults. Comput. J. 53(9): 1430-1446 (2010) - [c4]Michael A. Osborne, Roman Garnett, Stephen J. Roberts:
Active Data Selection for Sensor Networks with Faults and Changepoints. AINA 2010: 533-540 - [c3]Roman Garnett, Michael A. Osborne
Bayesian optimization for sensor set selection. IPSN 2010: 209-219
2000 – 2009
- 2009
- [c2]Roman Garnett, Michael A. Osborne, Stephen J. Roberts:
Sequential Bayesian prediction in the presence of changepoints. ICML 2009: 345-352 - 2008
- [c1]Michael A. Osborne
Towards Real-Time Information Processing of Sensor Network Data Using Computationally Efficient Multi-output Gaussian Processes. IPSN 2008: 109-120
Coauthor Index
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