Deep Sequential Models for Suicidal Ideation from Multiple Source Data I Peis, PM Olmos, C Vera-Varela, ML Barrigon, P Courtet, E Baca-Garcia, ... IEEE Journal of Biomedical and Health Informatics, 2019 | 18 | 2019 |
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo I Peis, C Ma, JM Hernández-Lobato Advances in Neural Information Processing Systems 35, 35839--35851, 2022 | 13 | 2022 |
Actigraphic recording of motor activity in depressed inpatients: a novel computational approach to prediction of clinical course and hospital discharge I Peis, JD López-Moríñigo, MM Pérez-Rodríguez, ML Barrigón, ... Scientific reports 10 (1), 17286, 2020 | 9 | 2020 |
Unsupervised learning of global factors in deep generative models I Peis, PM Olmos, A Artés-Rodríguez Pattern Recognition 134, 109130, 2023 | 6 | 2023 |
A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI D Castillo-Barnes, I Peis, FJ Martínez-Murcia, F Segovia, IA Illán, ... Frontiers in Neuroinformatics 11, 66, 2017 | 3 | 2017 |
MRI brain segmentation using hidden Markov random fields with alpha-stable distributions I Peis, IA Illán, FJ Martínez-Murcia, F Segovia, JM Górriz, J Ramírez, ... 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room …, 2016 | 3 | 2016 |
Variational Mixture of HyperGenerators for Learning Distributions Over Functions B Koyuncu, P Sanchez-Martin, I Peis, PM Olmos, I Valera International Conference on Machine Learning, 17660-17683, 2023 | 2 | 2023 |
Scalable physical source-to-field inference with hypernetworks B James, S Pollok, I Peis, J Frellsen, R Bjørk arXiv preprint arXiv:2405.05981, 2024 | | 2024 |
Advanced Inference and Representation Learning Methods in Variational Autoencoders I Peis Aznarte e-Archivo Universidad Carlos III de Madrid, 2023 | | 2023 |