no code implementations • 17 Jan 2023 • María Martínez-García, Fernando Moreno-Pino, Pablo M. Olmos, Antonio Artés-Rodríguez
Sleep constitutes a key indicator of human health, performance, and quality of life.
no code implementations • 8 Nov 2022 • Fernando Moreno-Pino, María Martínez-García, Pablo M. Olmos, Antonio Artés-Rodríguez
Psychiatric patients' passive activity monitoring is crucial to detect behavioural shifts in real-time, comprising a tool that helps clinicians supervise patients' evolution over time and enhance the associated treatments' outcomes.
1 code implementation • 12 Jan 2022 • Fernando Moreno-Pino, Emese Sükei, Pablo M. Olmos, Antonio Artés-Rodríguez
We introduce PyHHMM, an object-oriented open-source Python implementation of Heterogeneous-Hidden Markov Models (HHMMs).
1 code implementation • NeurIPS 2021 • Pablo Moreno-Muñoz, Antonio Artés-Rodríguez, Mauricio A. Álvarez
We present a framework for transfer learning based on modular variational Gaussian processes (GP).
no code implementations • 23 Aug 2021 • Aurora Cobo Aguilera, Pablo Martínez Olmos, Antonio Artés-Rodríguez, Fernando Pérez-Cruz
Language models (LM) have grown with non-stop in the last decade, from sequence-to-sequence architectures to the state-of-the-art and utter attention-based Transformers.
1 code implementation • 13 Jul 2021 • Fernando Moreno-Pino, Pablo M. Olmos, Antonio Artés-Rodríguez
In this paper, we propose a forecasting architecture that combines deep autoregressive models with a Spectral Attention (SA) module, which merges global and local frequency domain information in the model's embedded space.
1 code implementation • 12 Mar 2021 • Daniel Barrejón, Pablo M. Olmos, Antonio Artés-Rodríguez
Medical data sets are usually corrupted by noise and missing data.
1 code implementation • 15 Dec 2020 • Ignacio Peis, Pablo M. Olmos, Antonio Artés-Rodríguez
We present a novel deep generative model based on non i. i. d.
no code implementations • 14 Nov 2020 • Pablo Moreno-Muñoz, Lorena Romero-Medrano, Ángela Moreno, Jesús Herrera-López, Enrique Baca-García, Antonio Artés-Rodríguez
More than one million people commit suicide every year worldwide.
1 code implementation • 6 Oct 2020 • Pablo Moreno-Muñoz, Antonio Artés-Rodríguez, Mauricio A. Álvarez
We present a new framework for recycling independent variational approximations to Gaussian processes.
no code implementations • 24 Jul 2020 • Lorena Romero-Medrano, Pablo Moreno-Muñoz, Antonio Artés-Rodríguez
Bayesian change-point detection, together with latent variable models, allows to perform segmentation over high-dimensional time-series.
1 code implementation • 4 Jun 2020 • Aurora Cobo Aguilera, Antonio Artés-Rodríguez, Fernando Pérez-Cruz, Pablo Martínez Olmos
Deep learning requires regularization mechanisms to reduce overfitting and improve generalization.
no code implementations • 6 Nov 2019 • Ignacio Peis, Pablo M. Olmos, Constanza Vera-Varela, María Luisa Barrigón, Philippe Courtet, Enrique Baca-García, Antonio Artés-Rodríguez
This article presents a novel method for predicting suicidal ideation from Electronic Health Records (EHR) and Ecological Momentary Assessment (EMA) data using deep sequential models.
2 code implementations • 31 Oct 2019 • Pablo Moreno-Muñoz, Antonio Artés-Rodríguez, Mauricio A. Álvarez
We then demonstrate that it is possible to derive GP models over many types of sequential observations, either discrete or continuous and amenable to stochastic optimization.
1 code implementation • 22 Oct 2019 • Pablo Moreno-Muñoz, David Ramírez, Antonio Artés-Rodríguez
Change-point detection (CPD) aims to locate abrupt transitions in the generative model of a sequence of observations.
1 code implementation • 11 Sep 2018 • Pablo Moreno-Muñoz, David Ramírez, Antonio Artés-Rodríguez
This paper addresses the problem of change-point detection on sequences of high-dimensional and heterogeneous observations, which also possess a periodic temporal structure.
1 code implementation • NeurIPS 2018 • Pablo Moreno-Muñoz, Antonio Artés-Rodríguez, Mauricio A. Álvarez
We present a novel extension of multi-output Gaussian processes for handling heterogeneous outputs.
no code implementations • 13 Jul 2015 • Francisco Hernando-Gallego, Antonio Artés-Rodríguez
The relation between performance and stress is described by the Yerkes-Dodson Law but varies significantly between individuals.
no code implementations • 18 Jul 2014 • Pablo G. Moreno, Yee Whye Teh, Fernando Perez-Cruz, Antonio Artés-Rodríguez
Crowdsourcing has been proven to be an effective and efficient tool to annotate large datasets.