Items where authors include "Lawrence, N.D."

Article

Paleyes, A., Urma, R.-G. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2021) Challenges in deploying machine learning : a survey of case studies. arXiv. (Submitted)

Smith, M.T., Álvarez, M.A. and Lawrence, N.D. (2019) Differentially private regression and classification with sparse Gaussian processes. arXiv. (Submitted)

Smith, M.T., Álvarez, M.A. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2019) Gaussian process regression for binned data. arXiv. (Submitted)

Särkkä, S., Álvarez, M.A. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2018) Gaussian process latent force models for learning and stochastic control of physical systems. IEEE Transactions on Automatic Control. ISSN 0018-9286

Lake, B.M., Lawrence, N.D. orcid.org/0000-0001-9258-1030 and Tenenbaum, J.B. (2018) The emergence of organizing structure in conceptual representation. Cognitive Science, 42 (S3). pp. 809-832. ISSN 0364-0213

Smith, M.T., Zwiessele, M. and Lawrence, N.D. (2017) Differentially Private Gaussian Processes. arXiv. (Unpublished)

Lönnberg, T., Svensson, V., James, K.R. et al. (20 more authors) (2017) Single-cell RNA-seq and computational analysis using temporal mixture modeling resolves TH1/TFH fate bifurcation in malaria. Science Immunology, 2 (9). eaal2192. ISSN 2470-9468

Durrande, N., Hensman, J., Rattray, M. et al. (1 more author) (2016) Detecting periodicities with Gaussian processes. PeerJ Computer Science, 2. e50. ISSN 2376-5992

Damianou, A.C., Titsias, M.K. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2016) Variational inference for latent variables and uncertain inputs in Gaussian processes. Journal of Machine Learning Research, 17. ISSN 1532-4435

Mattos, C.L.C., Dai, Z., Damianou, A. et al. (3 more authors) (2016) Recurrent Gaussian Processes. arXiv. (Unpublished)

Damianou, A. and Lawrence, N.D. (2015) Semi-described and semi-supervised learning with Gaussian processes. (Unpublished)

Hensman, J. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2014) Nested Variational Compression in Deep Gaussian Processes. arXiv. (Unpublished)

Fusi, N., Lippert, C., Lawrence, N.D. orcid.org/0000-0001-9258-1030 et al. (1 more author) (2014) Warped linear mixed models for the genetic analysis of transformed phenotypes. Nature Communications , 5. 4890.

Hensman, J., Rattray, M. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2014) Fast Nonparametric Clustering of Structured Time-Series. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37 (2). pp. 383-393. ISSN 0162-8828

Alvarez, M.A. orcid.org/0000-0002-8980-4472, Luengo, D. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2013) Linear Latent Force Models Using Gaussian Processes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35 (11). pp. 2693-2705. ISSN 0162-8828

Hensman, J., Lawrence, N.D. orcid.org/0000-0001-9258-1030 and Rattray, M. (2013) Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters. BMC Bioinformatics, 14. 252. ISSN 1471-2105

Alvarez, M.A., Rosasco, L. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2012) Kernels for Vector-Valued Functions: a Review. Foundations and Trends® in Machine Learning, 4 (3). pp. 195-266. ISSN 1935-8237

Penfold, C.A., Brown, P.E., Lawrence, N.D. orcid.org/0000-0001-9258-1030 et al. (1 more author) (2012) Modeling Meiotic Chromosomes Indicates a Size Dependent Contribution of Telomere Clustering and Chromosome Rigidity to Homologue Juxtaposition. PLoS Computational Biology, 8 (5). e1002496. ISSN 1553-734X

Fusi, N., Stegle, O. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2012) Joint Modelling of Confounding Factors and Prominent Genetic Regulators Provides Increased Accuracy in Genetical Genomics Studies. PLoS Computational Biology, 8 (1). e1002330. ISSN 1553-734X

Kalaitzis, A.A. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2011) A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression. BMC Bioinformatics, 12. 180. ISSN 1471-2105

Proceedings Paper

Smith, M.T., Alvarez, M.A., Zwiessele, M. et al. (1 more author) (2018) Differentially private regression with Gaussian processes. In: Storkey, A. and Perez-Cruz, F., (eds.) Proceedings of the 21st International Conference on Artificial Intelligence and Statistics. International Conference on Artificial Intelligence and Statistics 2018, 09-11 Apr 2018, Lanzarote, Canary Islands. Proceedings of Machine Learning Research (84). PMLR , pp. 1195-1203.

Alvarez Lopez, M.A., Dai, Z. and Lawrence, N.D. (2017) Efficient modeling of latent information in supervised learning using Gaussian processes. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S. and Garnett, R., (eds.) Advances in Neural Information Processing Systems 30 (NIPS 2017) pre-proceedings. Advances in Neural Information Processing Systems (NIPS) 2017, 04-09 Dec 2017, Long Beach, CA. Massachusetts Institute of Technology Press , pp. 5131-5139.

Damianou, A., Ek, C.H., Boorman, L. orcid.org/0000-0001-5189-0232 et al. (2 more authors) (2015) A Top-Down Approach for a Synthetic Autobiographical Memory System. In: Biomimetic and Biohybrid Systems. 4th International Conference, Living Machines 2015, July 28 - 31, 2015, Barcelona, Spain. Lecture Notes in Computer Science, 9222 . Springer International Publishing , pp. 280-292. ISBN 978-3-319-22978-2

Damianou, A.C. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2013) Deep Gaussian Processes. In: Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics. Sixteenth International Conference on Artificial Intelligence and Statistics, 29 Apr - 01 May 2013, Scottsdale, AZ, USA. JMLR Workshop and Conference Proceedings, 31 . JMLR .