| Kernels for vector-valued functions: A review MA Alvarez, L Rosasco, ND Lawrence Foundations and Trends® in Machine Learning 4 (3), 195-266, 2012 | 861 | 2012 |
| Computationally efficient convolved multiple output Gaussian processes MA Alvarez, ND Lawrence The Journal of Machine Learning Research 12, 1459-1500, 2011 | 362 | 2011 |
| Sparse convolved Gaussian processes for multi-output regression M Alvarez, N Lawrence | 267 | 2008 |
| Latent force models M Alvarez, D Luengo, ND Lawrence Artificial Intelligence and Statistics, 9-16, 2009 | 204 | 2009 |
| Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison CD Zuluaga, MA Alvarez, E Giraldo Applied Energy 156, 321-330, 2015 | 150 | 2015 |
| Efficient multioutput Gaussian processes through variational inducing kernels M Álvarez, D Luengo, M Titsias, ND Lawrence Proceedings of the Thirteenth International Conference on Artificial …, 2010 | 147 | 2010 |
| Linear latent force models using Gaussian processes MA Alvarez, D Luengo, ND Lawrence IEEE transactions on pattern analysis and machine intelligence 35 (11), 2693 …, 2013 | 114 | 2013 |
| Heterogeneous multi-output Gaussian process prediction P Moreno-Muńoz, A Artés, M Alvarez Advances in neural information processing systems 31, 2018 | 74 | 2018 |
| Comparative analysis of physiological signals and electroencephalogram (EEG) for multimodal emotion recognition using generative models CA Torres-Valencia, HF Garcia-Arias, MAA Lopez, AA Orozco-Gutiérrez 2014 XIX Symposium on Image, Signal Processing and Artificial Vision, 1-5, 2014 | 55 | 2014 |
| SVM-based feature selection methods for emotion recognition from multimodal data C Torres-Valencia, M Álvarez-López, Á Orozco-Gutiérrez Journal on Multimodal User Interfaces 11, 9-23, 2017 | 51 | 2017 |
| Gaussian process latent force models for learning and stochastic control of physical systems S Särkkä, MA Alvarez, ND Lawrence IEEE Transactions on Automatic Control 64 (7), 2953-2960, 2018 | 47 | 2018 |
| Switched latent force models for movement segmentation M Alvarez, J Peters, N Lawrence, B Schölkopf Advances in neural information processing systems 23, 2010 | 39 | 2010 |
| Feature selection for multimodal emotion recognition in the arousal-valence space CA Torres, ÁA Orozco, MA Álvarez 2013 35th Annual International Conference of the IEEE Engineering in …, 2013 | 38 | 2013 |
| Differentially private regression with Gaussian processes MT Smith, MA Álvarez, M Zwiessele, ND Lawrence International Conference on Artificial Intelligence and Statistics, 1195-1203, 2018 | 34 | 2018 |
| Multi-task learning for aggregated data using Gaussian processes F Yousefi, MT Smith, M Alvarez Advances in Neural Information Processing Systems 32, 2019 | 25 | 2019 |
| Gaussian process dynamical models for multimodal affect recognition HF García, MA Álvarez, ÁÁ Orozco 2016 38th Annual International Conference of the IEEE Engineering in …, 2016 | 24 | 2016 |
| Non-linear process convolutions for multi-output Gaussian processes MA Álvarez, W Ward, C Guarnizo The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 20 | 2019 |
| Efficient modeling of latent information in supervised learning using gaussian processes Z Dai, M Álvarez, N Lawrence Advances in Neural Information Processing Systems 30, 2017 | 18 | 2017 |
| Automatic segmentation of nerve structures in ultrasound images using Graph Cuts and Gaussian processes JG González, MA Alvarez, AA Orozco 2015 37th Annual International Conference of the IEEE Engineering in …, 2015 | 15 | 2015 |
| Multi-task causal learning with Gaussian processes V Aglietti, T Damoulas, M Álvarez, J González Advances in Neural Information Processing Systems 33, 6293-6304, 2020 | 14 | 2020 |
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
