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

Article

Sheng, Y., Arbabi, H. orcid.org/0000-0001-8518-9022, Ward, W.O.C. et al. (2 more authors) (2025) City-scale residential energy consumption prediction with a multimodal approach. Scientific Reports, 15 (1). 5313. ISSN 2045-2322

Gutierrez, J.-J.G., Lau, E., Dharmapalan, S. et al. (4 more authors) (2024) Multi-output prediction of dose–response curves enables drug repositioning and biomarker discovery. npj Precision Oncology, 8 (1). 209. ISSN 2397-768X

Leroy, A. orcid.org/0000-0003-0806-8934, Gupta, V., Tint, M.T. orcid.org/0000-0002-9548-7186 et al. (10 more authors) (2024) Prospective prediction of childhood body mass index trajectories using multi-task Gaussian processes. International Journal of Obesity, 49 (2). pp. 340-347. ISSN 0307-0565

Smith, M.T., Ross, M., Ssematimba, J. et al. (3 more authors) (2023) Modelling calibration uncertainty in networks of environmental sensors. Journal of the Royal Statistical Society Series C: Applied Statistics, 72 (5). pp. 1187-1209. ISSN 0035-9254

Ma, C. orcid.org/0000-0002-8534-4720 and Álvarez, M.A. (2023) Large scale multi-output multi-class classification using Gaussian processes. Machine Learning, 112. pp. 1077-1106. ISSN 0885-6125

Smith, M.T., Grosse, K., Backes, M. et al. (1 more author) (2023) Adversarial vulnerability bounds for Gaussian process classification. Machine Learning, 112 (3). pp. 971-1009. ISSN 0885-6125

McDonald, T.M. and Álvarez, M.A. (2021) Compositional modeling of nonlinear dynamical systems with ODE-based random features. arXiv. (Submitted)

Ross, M., Smith, M.T. and Álvarez, M.A. (2021) Learning nonparametric Volterra kernels with Gaussian processes. arXiv. (Submitted)

Moreno-Muñoz, P., Artés-Rodríguez, A. and Álvarez, M.A. (2020) Recyclable Gaussian processes. arXiv, abs/2010.02554. (Submitted)

Aglietti, V., Damoulas, T., Álvarez, M.A. et al. (1 more author) (2020) Multi-task causal learning with Gaussian processes. arXiv. (Submitted)

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

Särkkä, S., Álvarez, M.A. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2019) Gaussian process latent force models for learning and stochastic control of physical systems. IEEE Transactions on Automatic Control, 64 (7). pp. 2953-2960. ISSN 0018-9286

Ward, W.O.C., Ryder, T., Prangle, D. et al. (1 more author) (2019) Variational bridge constructs for grey box modelling with 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)

Ward, W.O.C. orcid.org/0000-0002-4904-7294 and Álvarez, M.A. (2019) Variational bridge constructs for approximate Gaussian process regression. arXiv. (Submitted)

Vargas Cardona, H.D., Álvarez, M.A. orcid.org/0000-0002-8980-4472 and Orozco, Á.A. (2018) Multi-task learning for subthalamic nucleus identification in deep brain stimulation. International Journal of Machine Learning and Cybernetics, 9 (7). pp. 1181-1192. ISSN 1868-8071

López-Lopera, A.F. and Álvarez, M.A. orcid.org/0000-0002-8980-4472 (2017) Switched latent force models for reverse-engineering transcriptional regulation in gene expression data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16 (1). pp. 322-335. ISSN 1545-5963

Valencia, E.A. and Álvarez, M.A. orcid.org/0000-0002-8980-4472 (2017) Short-term time series prediction using Hilbert space embeddings of autoregressive processes. Neurocomputing. ISSN 0925-2312

Alvarado, P.A., Torres-Valencia, C.A., Orozco-Gutiérrez, Á. et al. (3 more authors) (2016) Modeling and behavior of the simulation of electric propagation during deep brain stimulation. DYNA (Colombia), 83 (198). pp. 49-58. ISSN 0012-7353

Proceedings Paper

McDonald, T.M., Ross, M., Smith, M.T. et al. (1 more author) (2023) Nonparametric gaussian process covariances via multidimensional convolutions. In: Ruiz, F., Dy, J. and van de Meent, J-W, (eds.) Proceedings of Machine Learning Research. International Conference on Artificial Intelligence and Statistics, 25-27 Apr 2023, Palau de Congressos, Valencia, Spain. ML Research Press , pp. 8279-8293.

Gahungu, P., Lanyon, C.W., Álvarez, M.A. et al. (3 more authors) (2022) Adjoint-aided inference of Gaussian process driven differential equations. In: Advances in Neural Information Processing Systems (NeurIPS 2022). 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 28 Nov - 09 Dec 2022, New Orleans, LA, USA. . ISBN 9781713871088

Moreno-Muñoz, P., Artés-Rodríguez, A. and Álvarez, M.A. (2019) Heterogeneous multi-output Gaussian process prediction. In: Bengio, S., Wallach, H., Larochelle, H., Grauman, K., Cesa-Bianchi, N. and Garnett, R., (eds.) Advances in Neural Information Processing Systems. Annual Conference on Neural Information Processing Systems 2018 (NeurIPS 2018), 03-08 Dec 2018, Montréal, Canada. Neural Information Processing Systems Foundation , pp. 6711-6720. ISBN 978-1-5108-8447-2

García, H.F., Álvarez, M.A. orcid.org/0000-0002-8980-4472 and Orozco, Á.A. (2017) Bayesian optimization for fitting 3D morphable models of brain structures. In: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2016. 21st Iberoamerican Congress, CIARP 2016, 08/11/2016-11/11/2016, Lima, Peru. Lecture Notes in Computer Science, 10125 . Springer Verlag , pp. 291-299. ISBN 9783319522760

Agudelo-España, D., Álvarez, M.A. orcid.org/0000-0002-8980-4472 and Orozco, Á.A. (2017) Definition and composition of motor primitives using latent force models and hidden Markov models. In: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2016. Iberoamerican Congress on Pattern Recognition, 08/11/2016-11/11/2016, Lima, Peru. Lecture Notes in Computer Science, 10125 . Springer Verlag , pp. 249-256. ISBN 9783319522760

Gómez-González, S., Álvarez, M.A. orcid.org/0000-0002-8980-4472, García, H.F. et al. (2 more authors) (2015) Discriminative training for Convolved Multiple-Output Gaussian processes. In: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. 20th Iberoamerican Congress, CIARP 2015, November 9-12, 2015, Montevideo, Uruguay. Lecture Notes in Computer Science book series (9423). , pp. 595-602. ISBN 978-3-319-25750-1

Zuluaga, C.D., Valencia, E.A., Álvarez, M.A. orcid.org/0000-0002-8980-4472 et al. (1 more author) (2015) A Parzen-based distance between probability measures as an alternative of summary statistics in Approximate Bayesian Computation. In: Image Analysis and Processing — ICIAP 2015. 18th International Conference, September 7-11, 2015, Genoa, Italy. Lecture Notes in Computer Science (9279). Springer , pp. 50-61. ISBN 978-3-319-23230-0

Preprint

Smith, M.T., Ssematimba, J., Álvarez, M.A. et al. (1 more author) (2019) Machine Learning for a low-cost air pollution network. [Preprint] (Submitted)