Michael A Osborne - Google Scholar Citations

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	All	Since 2014
Citations	8012	7377
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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
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
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Sarvapali D. (Gopal) RamchurnProfessor of Artificial Intelligence, University of SouthamptonVerified email at ecs.soton.ac.uk
Tom GunterDepartment of Engineering Science, University of OxfordVerified email at robots.ox.ac.uk
Chris. J. OatesChair in Statistics, Newcastle UniversityVerified email at ncl.ac.uk
François-Xavier BriolLecturer in Statistical Science, University College LondonVerified email at turing.ac.uk
David HoweyAssociate Professor, University of OxfordVerified email at eng.ox.ac.uk
Dino SejdinovicUniversity of OxfordVerified email at stats.ox.ac.uk
Philipp HennigUniversity of Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
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
Mark EbdenUniversity of OxfordVerified email at robots.ox.ac.uk
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Diego GranziolDphil student, Oxford UniversityVerified email at robots.ox.ac.uk
Jonathan M. DowningDPhil, University of OxfordVerified email at robots.ox.ac.uk
David DuvenaudAssistant Professor, University of TorontoVerified email at cs.toronto.edu

Michael A Osborne

Associate Professor, University of Oxford

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

Machine Learning Technological Change Probabilistic Numerics Bayesian Optimization Gaussian Processes


Title	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	5041	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	251	2013
Gaussian processes for global optimization MA Osborne, R Garnett, SJ Roberts 3rd International Conference on Learning and Intelligent Optimization (LION3 …, 2009	207	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	187	2012
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	169	2008
Technology at work CB Frey, M Osborne The Future of Innovation and Employment. Citi GPS: Global Perspectives …, 2015	148	2015
Probabilistic numerics and uncertainty in computations P Hennig, MA Osborne, M Girolami Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015	118	2015
The future of skills: Employment in 2030 H Bakhshi, JM Downing, MA Osborne, P Schneider Pearson, 2017	116	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	115	2015
Bayesian optimization for sensor set selection R Garnett, MA Osborne, SJ Roberts Proceedings of the 9th ACM/IEEE International Conference on Information …, 2010	108	2010
Bayesian Gaussian Processes for Sequential Prediction, Optimisation and Quadrature M Osborne PhD thesis, University of Oxford, 2010	100	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	87*	2019
Gaussian process regression for forecasting battery state of health RR Richardson, MA Osborne, DA Howey Journal of Power Sources 357, 209-219, 2017	75	2017
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, 2016	75	2016
Active learning of model evidence using Bayesian quadrature M Osborne, R Garnett, Z Ghahramani, DK Duvenaud, SJ Roberts, ... Advances in neural information processing systems, 46-54, 2012	72	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	61	2015
Real-Time Information Processing of Environmental Sensor Network Data MA Osborne, SJ Roberts, A Rogers, NR Jennings ACM Transactions on Sensor Networks 9 (1), 2012	60*	2012
Sequential Bayesian prediction in the presence of changepoints and faults R Garnett, MA Osborne, S Reece, A Rogers, SJ Roberts The Computer Journal 53 (9), 1430, 2010	60	2010
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, 2789-2797, 2014	50	2014
GLASSES: Relieving the myopia of Bayesian optimisation J González, M Osborne, ND Lawrence Journal of Machine Learning Research, 2016	48	2016

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