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
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
David HoweyProfessor of Engineering Science, University of OxfordVerified email at eng.ox.ac.uk
Vu NguyenAmazonVerified email at robots.ox.ac.uk
Dino SejdinovicProfessor of Statistical Machine Learning, University of AdelaideVerified email at adelaide.edu.au
Neale GibsonTrinity College Dublin, University of Dublin, IrelandVerified email at tcd.ie
Philipp HennigUniversity of TübingenVerified email at uni-tuebingen.de
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Xingchen WanGoogleVerified email at google.com
Robert R. RichardsonPostdoctoral researcher, 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
Sarvapali D. (Gopal) RamchurnProfessor of Artificial Intelligence, University of SouthamptonVerified email at ecs.soton.ac.uk
Xiaowen DongUniversity of OxfordVerified 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
Leon C. CamenzindRIKENVerified email at unibas.ch
Natalia AresOxford UniversityVerified email at eng.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


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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	16023	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	757	2013
The future of skills: Employment in 2030 H Bakhshi, J Downing, M Osborne, P Schneider Pearson, 2017	669	2017
Gaussian process regression for forecasting battery state of health RR Richardson, MA Osborne, DA Howey Journal of Power Sources 357, 209-219, 2017	616	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	393	2015
Gaussian processes for global optimization MA Osborne, R Garnett, SJ Roberts 3rd International Conference on Learning and Intelligent Optimization (LION3 …, 2009	356	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	344	2012
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	333	2018
Probabilistic numerics and uncertainty in computations P Hennig, MA Osborne, M Girolami Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015	314	2015
Technology at work: The future of innovation and employment CB Frey, M Osborne Citi GPS, 2015	305	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	236	2008
Technology at work v2. 0: The future is not what it used to be CB Frey, MA Osborne Citi GPS: Global Perspectives & Solutions, 2016	232	2016
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	218	2019
Bayesian optimization for sensor set selection R Garnett, MA Osborne, SJ Roberts Proceedings of the 9th ACM/IEEE International Conference on Information …, 2010	212	2010
Probabilistic integration FX Briol, CJ Oates, M Girolami, MA Osborne, D Sejdinovic Statistical Science 34 (1), 1-22, 2019	211*	2019
Battery health prediction under generalized conditions using a Gaussian process transition model RR Richardson, MA Osborne, DA Howey Journal of Energy Storage 23, 320-328, 2019	205	2019
Bayesian Gaussian Processes for Sequential Prediction, Optimisation and Quadrature M Osborne PhD thesis, University of Oxford, 2010	185	2010
Creativity vs robots: The creative economy and the future of employment H Bakhshi, CB Frey, M Osbourne Nesta, 2015	159	2015
GLASSES: Relieving the myopia of Bayesian optimisation J González, M Osborne, N Lawrence Artificial Intelligence and Statistics, 790-799, 2016	140	2016
Variational inference for Gaussian process modulated Poisson processes C Lloyd, T Gunter, M Osborne, S Roberts International Conference on Machine Learning, 1814-1822, 2015	137	2015

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