Search Results - "Peis, Ignacio"

A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI by Castillo-Barnes, Diego, Peis, Ignacio, Martínez-Murcia, Francisco J, Segovia, Fermín, Illán, Ignacio A, Górriz, Juan M, Ramírez, Javier, Salas-Gonzalez, Diego

“…A wide range of segmentation approaches assumes that intensity histograms extracted from magnetic resonance images (MRI) have a distribution for each brain…”
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Unsupervised learning of global factors in deep generative models by Peis, Ignacio, Olmos, Pablo M., Artés-Rodríguez, Antonio

“…•Learning global dependencies among observations in VAEs with a mixture prior and a global latent space.•Interpretability of the generative factors without…”
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Deep Sequential Models for Suicidal Ideation From Multiple Source Data by Peis, Ignacio, Olmos, Pablo M., Vera-Varela, Constanza, Barrigon, Maria Luisa, Courtet, Philippe, Baca-Garcia, Enrique, Artes-Rodriguez, Antonio

“…This paper presents a novel method for predicting suicidal ideation from electronic health records (EHR) and ecological momentary assessment (EMA) data using…”
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Actigraphic recording of motor activity in depressed inpatients: a novel computational approach to prediction of clinical course and hospital discharge by Peis, Ignacio, López-Moríñigo, Javier-David, Pérez-Rodríguez, M. Mercedes, Barrigón, Maria-Luisa, Ruiz-Gómez, Marta, Artés-Rodríguez, Antonio, Baca-García, Enrique

“…Depressed patients present with motor activity abnormalities, which can be easily recorded using actigraphy. The extent to which actigraphically recorded motor…”
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Relationship between olive oil consumption and ankle-brachial pressure index in a population at high cardiovascular risk by Sánchez-Quesada, Cristina, Toledo, Estefanía, González-Mata, Guadalupe, Ramos-Ballesta, Maria Isabel, Peis, José Ignacio, Martínez-González, Miguel Ángel, Salas-Salvadó, Jordi, Corella, Dolores, Fitó, Montserrat, Romaguera, Dora, Vioque, Jesús, Alonso-Gómez, Ángel M., Wärnberg, Julia, Martínez, J. Alfredo, Serra-Majem, Luís, Estruch, Ramon, Tinahones, Francisco J., Lapetra, José, Pintó, Xavier, Tur, Josep A., Garcia-Rios, Antonio, Cano-Ibáñez, Naomi, Matía-Martín, Pilar, Daimiel, Lidia, Sánchez-Rodríguez, Rubén, Vidal, Josep, Vázquez, Clotilde, Ros, Emilio, Hernández-Alonso, Pablo, Barragan, Rocío, Muñoz-Martínez, Julia, López, Meritxell, González-Palacios, Sandra, Vaquero-Luna, Jessica, Crespo-Oliva, Edelys, Zulet, M. Angeles, Díaz-González, Vanessa, Casas, Rosa, Fernandez-Garcia, José Carlos, Santos-Lozano, José Manuel, Galera, Ana, Ripoll-Vera, Tomás, Buil-Cosiales, Pilar, Canudas, Silvia, Martinez-Lacruz, Raul, Pérez-Vega, Karla-Alejandra, Rios, Ángel, Lloret-Macián, Rosario, Moreno-Rodriguez, Anai, Ruiz-Canela, Miguel, Babio, Nancy, Zomeño Fajardo, Maria Dolores, Gaforio, José J.

“…The aim of this study was to ascertain the association between the consumption of different categories of edible olive oils (virgin olive oils and olive oil)…”
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Scalable physical source-to-field inference with hypernetworks by James, Berian, Pollok, Stefan, Peis, Ignacio, Frellsen, Jes, Bjørk, Rasmus

“…We present a generative model that amortises computation for the field around e.g. gravitational or magnetic sources. Exact numerical calculation has either…”
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Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo by Peis, Ignacio, Ma, Chao, Hernández-Lobato, José Miguel

“…Variational Autoencoders (VAEs) have recently been highly successful at imputing and acquiring heterogeneous missing data. However, within this specific…”
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Variational Mixture of HyperGenerators for Learning Distributions Over Functions by Koyuncu, Batuhan, Sanchez-Martin, Pablo, Peis, Ignacio, Olmos, Pablo M, Valera, Isabel

“…Recent approaches build on implicit neural representations (INRs) to propose generative models over function spaces. However, they are computationally costly…”
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Unsupervised Learning of Global Factors in Deep Generative Models by Peis, Ignacio, Olmos, Pablo M, Artés-Rodríguez, Antonio

“…We present a novel deep generative model based on non i.i.d. variational autoencoders that captures global dependencies among observations in a fully…”
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Deep Sequential Models for Suicidal Ideation from Multiple Source Data by Peis, Ignacio, Olmos, Pablo M, Vera-Varela, Constanza, Barrigón, María Luisa, Courtet, Philippe, Baca-García, Enrique, Artés-Rodríguez, Antonio

“…Journal of Biomedical and Health Informatics, vol.23, no. 6, 2019 This article presents a novel method for predicting suicidal ideation from Electronic Health…”
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