James Hensman

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Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Mark van der WilkAssociate Professor, University of OxfordVerified email at cs.ox.ac.uk
Keith WordenUniversity of SheffieldVerified email at sheffield.ac.uk
Alexander G. D. G. MatthewsDeepMindVerified email at google.com
Magnus RattrayUniversity of ManchesterVerified email at manchester.ac.uk
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Nicolas DurrandePrincipal Scientist at MonumoVerified email at monumo.com
Vincent DutordoirUniversity of CambridgeVerified email at cam.ac.uk
ST JohnFinnish Center for Artificial Intelligence FCAI, Aalto UniversityVerified email at aalto.fi
Karen HolfordHonorary Distinguished Professor of Mechanical Engineering CardiffVerified email at cardiff.ac.uk
Mark J EatonCardiff UniversityVerified email at cf.ac.uk
Rhys PullinSenior Lecturer in Performance Engineering, Cardiff UniversityVerified email at cardiff.ac.uk
Artem ArtemevImperial College LondonVerified email at imperial.ac.uk
Stefanos EleftheriadisVerified email at amazon.com
Gareth PierceProfessor Electrical and Electronic Engineering, University of StrathclydeVerified email at strath.ac.uk
Hugh SalimbeniImperial College LondonVerified email at ic.ac.uk
Marc DeisenrothUniversity College LondonVerified email at ucl.ac.uk
Vincent AdamPompeu Fabra UniversityVerified email at gatsby.ucl.ac.uk
Nicolo FusiPartner Researcher, Microsoft ResearchVerified email at microsoft.com
Keisuke FujiiOak Ridge National LaboratoryVerified email at ornl.gov

James Hensman

Microsoft Research

Verified email at microsoft.com

machine learning probabilistic modelling biostatistics Gaussian processes approximate inference


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Gaussian processes for big data J Hensman, N Fusi, ND Lawrence Conference on Uncertainty in Artificial Intellegence, 282--290, 2013	1365	2013
Scalable Variational Gaussian Process Classification J Hensman, A Matthews, Z Ghahramani AISTATS 38, 2014	635	2014
GPflow: A Gaussian Process Library using TensorFlow. AGG Matthews, M Van Der Wilk, T Nickson, K Fujii, A Boukouvalas, ... J. Mach. Learn. Res. 18 (40), 1-6, 2017	548*	2017
Natural computing for mechanical systems research: A tutorial overview K Worden, WJ Staszewski, JJ Hensman Mechanical Systems and Signal Processing 25 (1), 4-111, 2011	324	2011
Variational Fourier Features for Gaussian Processes. J Hensman, N Durrande, A Solin J. Mach. Learn. Res. 18 (1), 5537-5588, 2017	210	2017
Locating acoustic emission sources in complex structures using Gaussian processes J Hensman, R Mills, SG Pierce, K Worden, M Eaton Mechanical Systems and Signal Processing 24 (1), 211-223, 2010	175	2010
On sparse variational methods and the Kullback-Leibler divergence between stochastic processes AGG Matthews, J Hensman, R Turner, Z Ghahramani AISTATS 51, 231-239, 2016	172*	2016
MCMC for variationally sparse Gaussian processes J Hensman, AGG Matthews, M Filippone, Z Ghahramani NIPS 2015, 2015	158	2015
Convolutional gaussian processes M van der Wilk, CE Rasmussen, J Hensman NeurIPS 2017, 2017	155	2017
GPy: A gaussian process framework in python J Hensman, N Fusi, R Andrade, N Durrande, A Saul, M Zwiessele, ...	149*	2012
The circadian clock in murine chondrocytes regulates genes controlling key aspects of cartilage homeostasis N Gossan, L Zeef, J Hensman, A Hughes, JF Bateman, L Rowley, ... Arthritis & Rheumatism 65 (9), 2334-2345, 2013	139	2013
Fast variational inference in the conjugate exponential family J Hensman, M Rattray, ND Lawrence NIPS 2012, 2012	130	2012
Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters J Hensman, ND Lawrence, M Rattray BMC bioinformatics 14 (1), 1-12, 2013	126	2013
Parameter estimation and model selection for a class of hysteretic systems using Bayesian inference K Worden, JJ Hensman Mechanical Systems and Signal Processing 32, 153-169, 2012	121	2012
Identification of Gaussian process state space models S Eleftheriadis, T Nicholson, M Deisenroth, J Hensman Advances in neural information processing systems 30, 2017	114	2017
A new methodology for automating acoustic emission detection of metallic fatigue fractures in highly demanding aerospace environments: An overview KM Holford, MJ Eaton, JJ Hensman, R Pullin, SL Evans, N Dervilis, ... Progress in Aerospace Sciences 90, 1-11, 2017	103	2017
A framework for interdomain and multioutput Gaussian processes M Van der Wilk, V Dutordoir, ST John, A Artemev, V Adam, J Hensman arXiv preprint arXiv:2003.01115, 2020	89	2020
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models H Salimbeni, S Eleftheriadis, J Hensman AISTATS, 2018	89	2018
Hoxa2 selectively enhances Meis binding to change a branchial arch ground state S Amin, IJ Donaldson, DA Zannino, J Hensman, M Rattray, M Losa, ... Developmental cell 32 (3), 265-277, 2015	85	2015
Learning Invariances using the Marginal Likelihood M van der Wilk, M Bauer, ST John, J Hensman NeurIPS 2018, 2018	84*	2018

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