Neil D. Lawrence - Google Scholar

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Citations	15517	9205
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Magnus RattrayUniversity of ManchesterVerified email at manchester.ac.uk
Andreas DamianouAmazon.comVerified email at amazon.com
Mauricio A. ÁlvarezUniversity of SheffieldVerified email at sheffield.ac.uk
Zhenwen DaiSpotifyVerified email at spotify.com
James HensmanPrincipal scientist, AmazonVerified email at amazon.com
Michalis TitsiasDeepMindVerified email at google.com
Guido SanguinettiReader in Informatics, University of EdinburghVerified email at inf.ed.ac.uk
Joaquin Quiñonero CandelaEngineering Director at FacebookVerified email at fb.com
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Marta MiloLecturer in Computational Biology, University of SheffieldVerified email at sheffield.ac.uk
Nicolò FusiSenior Principal Researcher, Microsoft ResearchVerified email at microsoft.com
Antti HonkelaAssociate Professor, University of HelsinkiVerified email at helsinki.fi
Javier GonzálezMicrosoft Research CambridgeVerified email at microsoft.com
Carl Henrik EkUniversity of CambridgeVerified email at cam.ac.uk
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinVerified email at amazon.de
Oliver StegleGerman Cancer Research Center (DKFZ) & EMBL HeidelbergVerified email at dkfz.de
David J FleetGoogle Brain; University of Toronto; Vector InstituteVerified email at cs.toronto.edu
David LuengoUniversidad Politécnica de Madrid (UPM)Verified email at upm.es
Raquel UrtasunAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Ralf HerbrichZalandoVerified email at zalando.de

Neil D. Lawrence

University of Cambridge

Verified email at cl.cam.ac.uk - Homepage

machine learning computational biology dimensionality reduction Gaussian processes probabilistic modelling


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Probabilistic non-linear principal component analysis with Gaussian process latent variable models N Lawrence Journal of machine learning research 6 (Nov), 1783-1816, 2005	989	2005
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	897*	2007
Gaussian process latent variable models for visualisation of high dimensional data ND Lawrence Advances in neural information processing systems, 329-336, 2004	866	2004
Dataset shift in machine learning J Quionero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence The MIT Press, 2009	681	2009
Gaussian processes for big data J Hensman, N Fusi, ND Lawrence arXiv preprint arXiv:1309.6835, 2013	645	2013
Wifi-slam using gaussian process latent variable models. B Ferris, D Fox, ND Lawrence IJCAI 7 (1), 2480-2485, 2007	594	2007
Fast sparse Gaussian process methods: The informative vector machine R Herbrich, ND Lawrence, M Seeger Advances in neural information processing systems, 625-632, 2003	580	2003
Deep gaussian processes A Damianou, N Lawrence Artificial Intelligence and Statistics, 207-215, 2013	567	2013
Kernels for vector-valued functions: A review MA Alvarez, L Rosasco, ND Lawrence arXiv preprint arXiv:1106.6251, 2011	446	2011
Fast forward selection to speed up sparse Gaussian process regression M Seeger, C Williams, N Lawrence Artificial Intelligence and Statistics 9, 2003	433	2003
Bayesian Gaussian process latent variable model M Titsias, ND Lawrence Proceedings of the Thirteenth International Conference on Artificial …, 2010	347	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	314	2004
Non-linear matrix factorization with Gaussian processes ND Lawrence, R Urtasun Proceedings of the 26th annual international conference on machine learning …, 2009	256	2009
Local distance preservation in the GP-LVM through back constraints ND Lawrence, J Quiñonero-Candela Proceedings of the 23rd international conference on Machine learning, 513-520, 2006	237	2006
Computationally efficient convolved multiple output Gaussian processes MA Álvarez, ND Lawrence The Journal of Machine Learning Research 12, 1459-1500, 2011	224	2011
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	209	2001
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	208	2009
Sparse convolved Gaussian processes for multi-output regression M Alvarez, ND Lawrence Advances in neural information processing systems, 57-64, 2009	191	2009
Semi-supervised learning via Gaussian processes ND Lawrence, MI Jordan Advances in neural information processing systems, 753-760, 2005	189	2005
Hierarchical Gaussian process latent variable models ND Lawrence, AJ Moore Proceedings of the 24th international conference on Machine learning, 481-488, 2007	183	2007

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