Session

DescriptionNumerical modeling of natural phenomena is an important aspect of modern research. Many tools have been developed which reproduce natural processes to offer in-silico predictions for a large variety of systems, including for example bio-physical phenomena, hydro- and aero-mechanical devices, or large-scale weather forecasting. A new tendency has recently emerged to replace ab-initio modeling of physical systems by heuristics-based predictions, to save significant computational cost. In this minisymposium, experts in the field will provide some perspectives regarding the application of machine learning approaches to this type of problems.