3 papers
stat.ML2025
Continuous Temporal Learning of Probability Distributions via Neural ODEs with Applications in Continuous Glucose Monitoring Data
Antonio Ãlvarez-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…
stat.ME2025
Multilevel functional distributional models with application to continuous glucose monitoring in diabetes clinical trials
Marcos Matabuena, Ciprian M. Crainiceanu
Continuous glucose monitoring (CGM) is a minimally invasive technology that measures blood glucose every few minutes for weeks or months at a time. CGM data are often collected in…
stat.ML2024
Conformal Prediction in Dynamic Biological Systems
Alberto Portela, Julio R. Banga, Marcos Matabuena
Uncertainty quantification (UQ) is the process of systematically determining and characterizing the degree of confidence in computational model predictions. In the context of syste…