Michael A Osborne

Cited by

	All	Since 2016
Citations	12117	10563
h-index	34	32
i10-index	71	66

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200920102011201220132014201520162017201820192020202133 64 51 80 117 271 560 885 1648 2191 2758 3002 56

Co-authors

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
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Alex RogersProfessor of Computer Science, University of OxfordVerified email at cs.ox.ac.uk
Nick JenningsVice-Provost (Research and Enterprise), Imperial CollegeVerified email at imperial.ac.uk
Sarvapali D. (Gopal) RamchurnProfessor of Artificial Intelligence, University of SouthamptonVerified email at ecs.soton.ac.uk
David HoweyAssociate Professor, University of OxfordVerified email at eng.ox.ac.uk
Tom GunterDepartment of Engineering Science, University of OxfordVerified email at robots.ox.ac.uk
Dino SejdinovicUniversity of OxfordVerified email at stats.ox.ac.uk
Chris. J. OatesChair in Statistics, Newcastle UniversityVerified email at ncl.ac.uk
François-Xavier BriolLecturer in Statistical Science, UCLVerified email at turing.ac.uk
Robert R. RichardsonPostdoctoral researcher, University of OxfordVerified email at eng.ox.ac.uk
Jack FitzsimonsDPhil (PhD) from University of OxfordVerified email at robots.ox.ac.uk
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Philipp HennigUniversity of Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Jonathan M. DowningDPhil, University of OxfordVerified email at robots.ox.ac.uk
Diego GranziolDphil student, Oxford UniversityVerified email at robots.ox.ac.uk
Mark EbdenUniversity of OxfordVerified email at robots.ox.ac.uk
Jan CalliessOxford UniversityVerified email at robots.ox.ac.uk

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


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The future of employment: How susceptible are jobs to computerisation? CB Frey, MA Osborne Technological forecasting and social change 114, 254-280, 2017	7360	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	356	2013
Gaussian processes for global optimization MA Osborne, R Garnett, SJ Roberts 3rd International Conference on Learning and Intelligent Optimization (LION3 …, 2009	261	2009
The future of skills: Employment in 2030 H Bakhshi, JM Downing, MA Osborne, P Schneider Pearson, 2017	244	2017
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	228	2012
The Future of Employment: How Susceptible are jobs to computerısatıon CB Frey, MA Osborne Septemper 17: http://www. oxfordmartin. ox. ac. uk/downloads/academic …, 2013	217	2013
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	195	2008
Technology at work: The future of innovation and employment CB Frey, M Osborne Citi GPS, 2015	185	2015
Probabilistic numerics and uncertainty in computations P Hennig, MA Osborne, M Girolami Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015	168	2015
Gaussian process regression for forecasting battery state of health RR Richardson, MA Osborne, DA Howey Journal of Power Sources 357, 209-219, 2017	162	2017
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	161	2015
Bayesian optimization for sensor set selection R Garnett, MA Osborne, SJ Roberts Proceedings of the 9th ACM/IEEE International Conference on Information …, 2010	142	2010
Bayesian Gaussian Processes for Sequential Prediction, Optimisation and Quadrature M Osborne PhD thesis, University of Oxford, 2010	133	2010
Technology at work v2. 0: The future is not what it used to be CB Frey, M Osborne, C Holmes, E Rahbari, R Garlick, G Friedlander, ... CityGroup and University of Oxford 338, 2016	129	2016
Probabilistic integration: A role in statistical computation? FX Briol, CJ Oates, M Girolami, MA Osborne, D Sejdinovic Statistical Science 34 (1), 1-22, 2019	125*	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, 46-54, 2012	99	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	89	2015
GLASSES: Relieving the myopia of Bayesian optimisation J González, M Osborne, N Lawrence Artificial Intelligence and Statistics, 790-799, 2016	76	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, 2789-2797, 2014	74	2014
The future of employment: how susceptible are jobs to computerisation? University of Oxford CB Frey, MA Osborne Oxford. Online verfügbar unter https://www. oxfordmartin. ox. ac. uk …, 2013	73	2013

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