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James Hensman
James Hensman
Microsoft Research
Verified email at microsoft.com
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
14722013
Scalable Variational Gaussian Process Classification
J Hensman, A Matthews, Z Ghahramani
AISTATS 38, 2014
7062014
GPflow: A Gaussian process library using TensorFlow
AGG Matthews, M Van Der Wilk, T Nickson, K Fujii, A Boukouvalas, P Le, ...
Journal of Machine Learning Research 18 (40), 1-6, 2017
6162017
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
3342011
Variational Fourier features for Gaussian processes
J Hensman, N Durrande, A Solin
Journal of Machine Learning Research 18 (151), 1-52, 2018
2272018
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
192*2016
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
1872010
MCMC for variationally sparse Gaussian processes
J Hensman, AGG Matthews, M Filippone, Z Ghahramani
NIPS 2015, 2015
1632015
GPy: A gaussian process framework in python
J Hensman, N Fusi, R Andrade, N Durrande, A Saul, M Zwiessele, ...
163*2012
Convolutional Gaussian processes
M van der Wilk, CE Rasmussen, J Hensman
NeurIPS 2017, 2017
1592017
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
1492013
Fast variational inference in the conjugate exponential family
J Hensman, M Rattray, ND Lawrence
NIPS 2012, 2012
1322012
Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters
J Hensman, ND Lawrence, M Rattray
BMC bioinformatics 14, 1-12, 2013
1262013
Identification of Gaussian process state space models
S Eleftheriadis, T Nicholson, M Deisenroth, J Hensman
Advances in neural information processing systems 30, 2017
1242017
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
1222012
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
1122017
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
972020
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models
H Salimbeni, S Eleftheriadis, J Hensman
AISTATS, 2018
952018
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
892015
Learning Invariances using the Marginal Likelihood
M van der Wilk, M Bauer, ST John, J Hensman
NeurIPS 2018, 2018
872018
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