2 citations · 2 across the 7 of their papers we have counts for
3 papers · 1 filter
Gaussian mixture models in Hilbert spaces via kernel methods
Daniel López-Montero, Antonio Álvarez-López, Marcos Matabuena
Modern datasets across many disciplines increasingly consist of time-evolving, potentially infinite-dimensional random objects, such as dynamic functional data, which are naturally…
Continuous-Time Learning of Probability Distributions: A Case Study in a Digital Trial of Young Children with Type 1 Diabetes
Antonio Álvarez-López, Marcos Matabuena
Understanding how biomarker distributions evolve over time is a central challenge in digital health and chronic disease monitoring. In diabetes, changes in the distribution of gluc…
Continuous Temporal Learning of Probability Distributions via Neural ODEs with Applications in Continuous Glucose Monitoring Data
Antonio Álvarez-López, Marcos Matabuena
Modeling the dynamics of probability distributions from time-dependent data samples is a fundamental problem in many fields, including digital health. The goal is to analyze how th…