Article accepted for publication in Neural Networks

Title Regularizing transformers with deep probabilistic layers Authors Aurora Cobo Aguilera, Pablo M. Olmos, Antonio Artés-Rodríguez and Fernando Pérez-Cruz Abstract Language models (LM) have grown non-stop in the last decade, from sequence-to-sequence architectures to attention-based Transformers. However, regularization is not deeply studied in those structures. In this work, we use a Gaussian Mixture Variational Autoencoder…

Doctoral Thesis Defense of Emese Sükei

Title: “A Step Towards Advancing Digital Phenotyping In Mental Healthcare” Advisor: Antonio Artés Rodríguez. ABSTRACT Smartphones and wrist-wearable devices have penetrated our lives in recent years. According to published statistics, nearly 84% of the world’s population owns a smartphone, and almost 10% own a wearable device today (2022). These devices continuously generate various data sources…

Doctoral Thesis Defense of Lorena Romero Medrano

Title: Change-Point Detection Methods for Behavioral Shift Recognition in Mental Healthcare Author: Lorena Romero (GTS) ABSTRACT Human behavior analysis has been approached from different perspectives along time. In recent years, the emergence of new technologies and digitalization advances have risen as an alternative tool for behavior characterization, as well as for the detection of changes over time. In particular,…

Doctoral Thesis Defense of Pablo Bonilla Escribano

Title: “Objective Assessment of Psychiatric Patients via Machine Learning” Advisor: Antonio Artés Rodríguez. ABSTRACT Mental disorders are still a source of not-well-understood human suffering. They affect one out of four people in the world, and they are more costly to treat than cancer and diabetes together. One of the reasons of the high economic burden…

Doctoral Thesis Defense of Aurora Cobo Aguilera

Title: “Probabilistic Models and Natural Language Processing in Health” Advisor: Antonio Artés Rodríguez. ABSTRACT We are living the Artificial Intelligence (AI) era. Whatever we want, we are surrounded by technology, computers, intelligent devices, and incredible machines able to perform more and more complex activities from our daily routine, from a writing predictor to a face…

Doctoral Thesis Defense of Sara Pérez Vieites

Title: “Nested filtering methods for Bayesian inference in state space models” Advisor: Joaquín Míguez Arenas. ABSTRACT A common feature to many problems in some of the most active fields of science is the need to calibrate (i.e., estimate the parameters) and then forecast the time evolution of high-dimensional dynamical systems using sequentially collected data. In…

Advances Methods for Orbital Uncertainty Characterization Applied to Space Surveillance and Tracking’s Industrial Doctorate

In this aid, the beneficiary is Alejandro Cano Sánchez and the abstract of the project is the following. The project is focused on the analysis and development of advanced methods for orbital uncertainty characterization applied to space surveillance and tracking of space debris, including the following aspects: modelling of the uncertainty in dynamical models and…

ESPECTRO’s INDUSTRIAL DOCTORATE

In this aid, the beneficiary is Arturo Armario Romero and the abstract of the project is the following. The goal of this project, named as ESPECTRO, is to provide eB2 with cutting-edge tools to combine and learn from multi-modal information. On the one hand, by providing classical methods with larger expressivity using BNP/ARD priors combined…