Neil D. Lawrence
Neil D. Lawrence
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Cited by
Cited by
Dataset shift in machine learning
J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence
Mit Press, 2022
Gaussian processes for big data
J Hensman, N Fusi, ND Lawrence
arXiv preprint arXiv:1309.6835, 2013
Deep Gaussian processes
A Damianou, ND Lawrence
Artificial intelligence and statistics, 207-215, 2013
Probabilistic non-linear principal component analysis with Gaussian process latent variable models.
N Lawrence
Journal of machine learning research 6 (11), 2005
Gaussian process latent variable models for visualisation of high dimensional data
N Lawrence
Advances in neural information processing systems 16, 2003
Kernels for vector-valued functions: A review
MA Alvarez, L Rosasco, ND Lawrence
Foundations and Trends® in Machine Learning 4 (3), 195-266, 2012
Wifi-slam using gaussian process latent variable models.
B Ferris, D Fox, ND Lawrence
IJCAI 7 (1), 2480-2485, 2007
Fast sparse Gaussian process methods: The informative vector machine
N Lawrence, M Seeger, R Herbrich
Advances in neural information processing systems 15, 2002
Variational information distillation for knowledge transfer
S Ahn, SX Hu, A Damianou, ND Lawrence, Z Dai
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
Fast forward selection to speed up sparse Gaussian process regression
MW Seeger, CKI Williams, ND Lawrence
International Workshop on Artificial Intelligence and Statistics, 254-261, 2003
Bayesian Gaussian process latent variable model
M Titsias, ND Lawrence
Proceedings of the thirteenth international conference on artificial …, 2010
Learning to learn with the informative vector machine
ND Lawrence, JC Platt
Proceedings of the twenty-first international conference on Machine learning, 65, 2004
Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling
P Perdikaris, M Raissi, A Damianou, ND Lawrence, GE Karniadakis
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2017
Batch Bayesian optimization via local penalization
J González, Z Dai, P Hennig, N Lawrence
Artificial intelligence and statistics, 648-657, 2016
Challenges in deploying machine learning: a survey of case studies
A Paleyes, RG Urma, ND Lawrence
ACM computing surveys 55 (6), 1-29, 2022
Computationally efficient convolved multiple output Gaussian processes
MA Alvarez, ND Lawrence
The Journal of Machine Learning Research 12, 1459-1500, 2011
Local distance preservation in the GP-LVM through back constraints
ND Lawrence, J Quinonero-Candela
Proceedings of the 23rd international conference on Machine learning, 513-520, 2006
Non-linear matrix factorization with Gaussian processes
ND Lawrence, R Urtasun
Proceedings of the 26th annual international conference on machine learning …, 2009
Sparse convolved Gaussian processes for multi-output regression
M Alvarez, N Lawrence
Advances in neural information processing systems 21, 2008
Advances in Neural Information Processing Systems
Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger
Inc.: Red Hook, NY, USA 27, 2014
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