James Hensman

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Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Keith WordenUniversity of SheffieldVerified email at sheffield.ac.uk
Alexander G. D. G. MatthewsDeepMindVerified email at google.com
Mark van der WilkImperial College LondonVerified email at imperial.ac.uk
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 DurrandeResearch Lead at Shift LabVerified email at shiftlab.ai
Vincent DutordoirUniversity of CambridgeVerified email at cam.ac.uk
ST JohnFinnish Center for Artificial Intelligence FCAI, Aalto UniversityVerified email at aalto.fi
Karen HolfordProfessor 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 EleftheriadisApplied scientist at AmazonVerified 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
Richard E TurnerProfessor, University of CambridgeVerified email at cam.ac.uk

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	1250	2013
Scalable Variational Gaussian Process Classification J Hensman, A Matthews, Z Ghahramani AISTATS 38, 2014	563	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	549*	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	310	2011
Variational Fourier Features for Gaussian Processes. J Hensman, N Durrande, A Solin J. Mach. Learn. Res. 18 (1), 5537-5588, 2017	189	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	167	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	157*	2016
MCMC for variationally sparse Gaussian processes J Hensman, AGG Matthews, M Filippone, Z Ghahramani NIPS 2015, 2015	148	2015
Convolutional gaussian processes M van der Wilk, CE Rasmussen, J Hensman NeurIPS 2017, 2017	140	2017
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	132	2013
Fast variational inference in the conjugate exponential family J Hensman, M Rattray, ND Lawrence NIPS 2012, 2012	126	2012
GPy: A gaussian process framework in python J Hensman, N Fusi, R Andrade, N Durrande, A Saul, M Zwiessele, ...	126*	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	116	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	114	2012
Identification of Gaussian process state space models S Eleftheriadis, T Nicholson, M Deisenroth, J Hensman Advances in neural information processing systems 30, 2017	101	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	92	2017
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	87	2015
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models H Salimbeni, S Eleftheriadis, J Hensman AISTATS, 2018	84	2018
Nested variational compression in deep Gaussian processes J Hensman, ND Lawrence arXiv preprint arXiv:1412.1370, 2014	81	2014
Genome-wide occupancy links Hoxa2 to Wnt–β-catenin signaling in mouse embryonic development IJ Donaldson, S Amin, JJ Hensman, E Kutejova, M Rattray, N Lawrence, ... Nucleic acids research 40 (9), 3990-4001, 2012	78	2012

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