MS004 Advancements in Time Evolution Operators in Scientific Machine Learning
Main Organizer:
Mr.
Matteo Caldana
(
Politecnico di Milano
, Italy
)
Chaired by:
Mr. Matteo Caldana (Politecnico di Milano , Italy) , Dr. Giovanni Ziarelli (Politecnico di Milano , Italy)
Mr. Matteo Caldana (Politecnico di Milano , Italy) , Dr. Giovanni Ziarelli (Politecnico di Milano , Italy)
Scheduled presentations:
-
Data-driven Closure Strategies for Parametrized Reduced Order Models via Deep Operator Networks
-
A CNN-LSTM Approach for Parameter Estimation in a Time-Dependent PDE Model for Metal Battery Cycling
-
A Variational Bayesian Method for Autoregressive and Recurrent Models
-
Learning High-dimensional Ionic Model Dynamics Using Fourier Neural Operators
-
Scientific Machine Learning Approaches to Cardiac Inverse Problems for Reconstructing Stimuli and Ischemia from Pseudo-ECG
-
Cultural Heritage Conservation: a framework based on PINNs and ROMs
