Michael A Osborne

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Stephen RobertsProfessor of Engineering Science (Machine Learning, Information Engineering), University of OxfordVerified email at robots.ox.ac.uk
Carl Benedikt FreyOxford UniversityVerified email at oxfordmartin.ox.ac.uk
Roman GarnettWashington University in St. LouisVerified email at wustl.edu
Neale GibsonAstrophysics research fellow, ESOVerified email at eso.org
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Dino SejdinovicAssociate Professor, University of OxfordVerified email at stats.ox.ac.uk
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
David HoweyProfessor of Engineering Science, University of OxfordVerified email at eng.ox.ac.uk
Alex RogersProfessor of Computer Science, University of OxfordVerified email at cs.ox.ac.uk
Nick JenningsVice-Chancellor and President, Loughborough UniversityVerified email at lboro.ac.uk
Vu NguyenAmazon AdelaideVerified email at robots.ox.ac.uk
Sarvapali D. (Gopal) RamchurnProfessor of Artificial Intelligence, University of SouthamptonVerified email at ecs.soton.ac.uk
Robert R. RichardsonPostdoctoral researcher, University of OxfordVerified email at eng.ox.ac.uk
Philipp HennigUniversity of Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Tom GunterDepartment of Engineering Science, University of OxfordVerified email at robots.ox.ac.uk
Chris. J. OatesNewcastle UniversityVerified email at ncl.ac.uk
François-Xavier BriolLecturer in Statistical Science, UCLVerified email at turing.ac.uk
Xiaowen DongUniversity of Oxford, Massachusetts Institute of TechnologyVerified email at robots.ox.ac.uk
G A D BriggsProfessor of Nanomaterials, University of OxfordVerified email at materials.ox.ac.uk
Dominic LennonCo-founder and Head of Quantum Technologies, QuantrolOxVerified email at quantrolox.com

Michael A Osborne

Professor of Machine Learning, University of Oxford

Verified email at robots.ox.ac.uk - Homepage

Machine Learning Technological Change Probabilistic Numerics Bayesian Optimization Gaussian Processes


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The future of employment: How susceptible are jobs to computerisation? CB Frey, MA Osborne Technological forecasting and social change 114, 254-280, 2017	10510	2017
Gaussian processes for time-series modelling S Roberts, M Osborne, M Ebden, S Reece, N Gibson, S Aigrain Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2013	505	2013
The future of skills: Employment in 2030 H Bakhshi, JM Downing, MA Osborne, P Schneider Pearson, 2017	399	2017
Gaussian process regression for forecasting battery state of health RR Richardson, MA Osborne, DA Howey Journal of Power Sources 357, 209-219, 2017	308	2017
Gaussian processes for global optimization MA Osborne, R Garnett, SJ Roberts 3rd International Conference on Learning and Intelligent Optimization (LION3 …, 2009	295	2009
A Gaussian process framework for modelling instrumental systematics: application to transmission spectroscopy NP Gibson, S Aigrain, S Roberts, TM Evans, M Osborne, F Pont Monthly notices of the royal astronomical society 419 (3), 2683-2694, 2012	278	2012
A Gaussian process framework for modelling stellar activity signals in radial velocity data V Rajpaul, S Aigrain, MA Osborne, S Reece, S Roberts Monthly Notices of the Royal Astronomical Society 452 (3), 2269-2291, 2015	247	2015
Technology at work: The future of innovation and employment CB Frey, M Osborne Citi GPS, 2015	232	2015
Probabilistic numerics and uncertainty in computations P Hennig, MA Osborne, M Girolami Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015	224	2015
Towards real-time information processing of sensor network data using computationally efficient multi-output Gaussian processes MA Osborne, SJ Roberts, A Rogers, SD Ramchurn, NR Jennings Proceedings of the 7th international conference on Information processing in …, 2008	212	2008
Technology at work v2. 0: The future is not what it used to be CB Frey, MA Osborne Citigroup, 2016	168	2016
Bayesian optimization for sensor set selection R Garnett, MA Osborne, SJ Roberts Proceedings of the 9th ACM/IEEE International Conference on Information …, 2010	168	2010
Probabilistic integration: a role in statistical computation? FX Briol, CJ Oates, M Girolami, MA Osborne, D Sejdinovic Statistical Science 34 (1), 1-22, 2019	156*	2019
Bayesian Gaussian Processes for Sequential Prediction, Optimisation and Quadrature M Osborne PhD thesis, University of Oxford, 2010	149	2010
Gaussian Process Regression for In Situ Capacity Estimation of Lithium-Ion Batteries RR Richardson, CR Birkl, MA Osborne, DA Howey IEEE Transactions on Industrial Informatics 15 (1), 127-138, 2018	141	2018
On the limitations of representing functions on sets E Wagstaff, F Fuchs, M Engelcke, I Posner, MA Osborne International Conference on Machine Learning, 6487-6494, 2019	108	2019
Active learning of model evidence using Bayesian quadrature M Osborne, R Garnett, Z Ghahramani, DK Duvenaud, SJ Roberts, ... Advances in neural information processing systems 25, 2012	107	2012
Variational inference for Gaussian process modulated Poisson processes C Lloyd, T Gunter, M Osborne, S Roberts International Conference on Machine Learning, 1814-1822, 2015	106	2015
GLASSES: Relieving the myopia of Bayesian optimisation J González, M Osborne, N Lawrence Artificial Intelligence and Statistics, 790-799, 2016	100	2016
Sampling for inference in probabilistic models with fast Bayesian quadrature T Gunter, MA Osborne, R Garnett, P Hennig, SJ Roberts Advances in neural information processing systems 27, 2014	87	2014

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