3 papers
math.NA2025
Cardiocirculatory Computational Models for the Study of Hypertension
Simone Celora, Andrea Tonini, Francesco Regazzoni +3
In this work, we develop patient-specific cardiocirculatory models with the aim of building Digital Twins for hypertension. In particular, in our pathophysiology-based framework, w…
cs.LG2025
Enhanced uncertainty quantification variational autoencoders for the solution of Bayesian inverse problems
Andrea Tonini, Luca Dede'
Among other uses, neural networks are a powerful tool for solving deterministic and Bayesian inverse problems in real-time, where variational autoencoders, a specialized type of ne…
math.NA2025
Improvements on uncertainty quantification with variational autoencoders
Andrea Tonini, Tan Bui-Thanh, Francesco Regazzoni +2
Inverse problems aim to determine model parameters of a mathematical problem from given observational data. Neural networks can provide an efficient tool to solve these problems. I…