This workshop is focused on the review of recent algorithmic and mathematical advances and the development of new research directions for Mathematical Model Approximations via RAMSES in the setting of parametrized partial differential equations with sparse and noisy data in high-dimensional parameter spaces.
Organising committee: SISSA mathLab team.
Scientific objectives and novelty of the workshop: The workshop focuses on four promising approaches for near-future improvements in the way model approximation in the partial differential equation setting is carried out. The central objective of the workshop is to gather together both senior and junior researchers
As opposed to other approximation/data-science/machine learning conferences, RAMSES features a poster blitz and a poster session entirely focused on junior participants, who will gain visibility and interact with experts.
Another important feature of RAMSES is that at the end of the second and third day a discussion session will take place. At these sessions, participants will review the talks of the day and discuss what are the most important and promising research directions. The discussions will be facilitated by a panel of selected speakers, non-speaking experts and funding agency personnel.
Expected outcome and impact of workshop:
The event is also among the proESOF initiatives.
It is also organized in cooperation with SISSA SIAM student chapter.