IS038A Model Order Reduction, Scientific Machine Learning and Uncertainty Quantification for Large Scale, Complex Geometry and Multi-physics Problems I
Main Organizer: Prof. Giovanni Stabile ( Sant'Anna School of Advanced Studies , Italy )
Chaired by:
Prof. Giovanni Stabile (Sant'Anna School of Advanced Studies , Italy) , Prof. Bojana Rosic (University of Twente , Netherlands)
Prof. Giovanni Stabile (Sant'Anna School of Advanced Studies , Italy) , Prof. Bojana Rosic (University of Twente , Netherlands)
Scheduled presentations:
-
Domain decomposition methods for large neural networks in high dimensional multi-physics problems
-
Chain-ROM: Fluid-Fluid Coupled Reduced Order Models (ROM) for Turbulent Flow
-
Predicting the Onset and Progression of Atherosclerotic Plaques in Carotid Arteries through CFD simulations: UQ and Stochastic Sensitivity Analysis to Geometric and Clinical Parameters
-
Enhancing Patient-Specific Cardiovascular Flow Modeling with Stochastic Data Assimilation
-
Domain Decomposition Reduced Order Model for Large Scale Industrial Facilities Consisting of Repeating Subdomains
-
Graph-Based Machine Learning Approaches for Model Order Reduction
-
Model-based Co-simulation of Non-smooth Mechanical Systems