| Kernels for vector-valued functions: A review MA Alvarez, L Rosasco, ND Lawrence Foundations and Trends® in Machine Learning 4 (3), 195-266, 2012 | 892 | 2012 |
| Computationally efficient convolved multiple output Gaussian processes MA Alvarez, ND Lawrence The Journal of Machine Learning Research 12, 1459-1500, 2011 | 374 | 2011 |
| Sparse convolved Gaussian processes for multi-output regression M Alvarez, N Lawrence | 277 | 2008 |
| Latent force models M Alvarez, D Luengo, ND Lawrence Artificial Intelligence and Statistics, 9-16, 2009 | 211 | 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 | 153 | 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 | 151 | 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 | 118 | 2013 |
| Heterogeneous multi-output Gaussian process prediction P Moreno-Muñoz, A Artés, M Alvarez Advances in neural information processing systems 31, 2018 | 84 | 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 | 56 | 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 | 54 | 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 | 48 | 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 | 36 | 2018 |
| Multi-task learning for aggregated data using Gaussian processes F Yousefi, MT Smith, M Alvarez Advances in Neural Information Processing Systems 32, 2019 | 26 | 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 | 25 | 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 | 23 | 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 | 20 | 2017 |
| 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 | 18 | 2020 |
| Bayesian probabilistic power flow analysis using Jacobian approximate Bayesian computation CD Zuluaga, MA Alvarez IEEE Transactions on Power Systems 33 (5), 5217-5225, 2018 | 17 | 2018 |
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
