Items where authors include "Alvarez, M.A."

Article

Gil-Gonzalez, J., Giraldo, J.-J., Alvarez-Meza, A.M. et al. (2 more authors) (2021) Correlated chained Gaussian processes for datasets with multiple annotators. IEEE Transactions on Neural Networks and Learning Systems, 34 (8). pp. 4514-4528. ISSN 2162-237X

Smith, M.T., Alvarez, M.A. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2021) Differentially private regression and classification with sparse Gaussian processes. Journal of Machine Learning Research, 22. 188. ISSN 1532-4435

Lopez-Lopera, A.F., Durrande, N. and Alvarez, M.A. (2021) Physically-inspired Gaussian process models for post-transcriptional regulation in Drosophila. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18 (2). pp. 656-666. ISSN 1545-5963

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

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

Proceedings Paper

Ward, W.O.C. orcid.org/0000-0002-4904-7294, Ryder, T., Prangle, D. et al. (1 more author) (2020) Black-box inference for non-linear latent force models. In: Chiappa, S. and Calandra, R., (eds.) International Conference on Artificial Intelligence and Statistics. International Conference on Artificial Intelligence and Statistics, 26-28 Aug 2020, Virtual conference. PMLR - Proceedings of Machine Learning Research , pp. 3088-3098.

Yousefi, F., Smith, M.T. and Alvarez, M.A. (2019) Multi-task Learning for aggregated data using Gaussian processes. In: Wallach, H.M., Larochelle, H., Beygelzimer, A., d'Alché-Buc, F., Fox, E.B. and Garnett, R., (eds.) Advances in Neural Information Processing Systems 32 (NeurIPS 2019). 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), 08-14 Dec 2019, Vancouver, Canada. , pp. 15050-15060. ISBN 9781713807933

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.

Cardona, H.D.V., Alvarez, M.A. and Orozco, A.A. (2015) Generalized Wishart processes for interpolation over diffusion tensor fields. In: Advances in Visual Computing. 11th International Symposium, ISVC 2015, December 14-16, 2015, Las Vegas, NV, USA. Lecture Notes in Computer Science (9475). Springer , pp. 499-508. ISBN 978-3-319-27862-9