Neil D. Lawrence
Neil D. Lawrence
University of Cambridge
Verified email at cl.cam.ac.uk - Homepage
Title
Cited by
Cited by
Year
Probabilistic non-linear principal component analysis with Gaussian process latent variable models.
N Lawrence, A Hyvärinen
Journal of machine learning research 6 (11), 2005
10752005
Gaussian process latent variable models for visualisation of high dimensional data.
ND Lawrence
Nips 2, 5, 2003
9472003
Gaussian process dynamical models for human motion
JM Wang, DJ Fleet, A Hertzmann
IEEE transactions on pattern analysis and machine intelligence 30 (2), 283-298, 2007
8772007
Dataset shift in machine learning
J Quionero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence
The MIT Press, 2009
8122009
Gaussian processes for big data
J Hensman, N Fusi, ND Lawrence
arXiv preprint arXiv:1309.6835, 2013
7562013
Deep gaussian processes
A Damianou, ND Lawrence
Artificial intelligence and statistics, 207-215, 2013
6832013
Wifi-slam using gaussian process latent variable models.
B Ferris, D Fox, ND Lawrence
IJCAI 7 (1), 2480-2485, 2007
6282007
Fast sparse Gaussian process methods: The informative vector machine
N Lawrence, M Seeger, R Herbrich
Proceedings of the 16th annual conference on neural information processing …, 2003
6232003
Kernels for vector-valued functions: A review
MA Alvarez, L Rosasco, ND Lawrence
arXiv preprint arXiv:1106.6251, 2011
5312011
Fast forward selection to speed up sparse Gaussian process regression
M Seeger, C Williams, N Lawrence
Artificial Intelligence and Statistics 9, 2003
4882003
Bayesian Gaussian process latent variable model
M Titsias, ND Lawrence
Proceedings of the Thirteenth International Conference on Artificial …, 2010
4102010
Learning to learn with the informative vector machine
ND Lawrence, JC Platt
Proceedings of the twenty-first international conference on Machine learning, 65, 2004
3352004
Non-linear matrix factorization with Gaussian processes
ND Lawrence, R Urtasun
Proceedings of the 26th annual international conference on machine learning …, 2009
2712009
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
2592006
Computationally efficient convolved multiple output Gaussian processes
MA Alvarez, ND Lawrence
The Journal of Machine Learning Research 12, 1459-1500, 2011
2512011
A critical role for phosphatase haplodeficiency in the selective suppression of deletion 5q MDS by lenalidomide
S Wei, X Chen, K Rocha, PK Epling-Burnette, JY Djeu, Q Liu, J Byrd, ...
Proceedings of the National Academy of Sciences 106 (31), 12974-12979, 2009
2172009
Estimating a kernel fisher discriminant in the presence of label noise
N Lawrence, B Schölkopf
18th International Conference on Machine Learning (ICML 2001), 306-306, 2001
2162001
Sparse Convolved Gaussian Processes for Multi-output Regression.
MA Alvarez, ND Lawrence
NIPS 21, 57-64, 2008
2102008
Hierarchical Gaussian process latent variable models
ND Lawrence, AJ Moore
Proceedings of the 24th international conference on Machine learning, 481-488, 2007
1982007
When training and test sets are different: characterizing learning transfer
A Storkey
Dataset shift in machine learning 30, 3-28, 2009
1952009
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