MS030A Mini Symposium: methodological aspects of machine learning for PDE ASPECTS OF MACHINE LEARNING FOR PDE I
Main Organizer:
Dr.
emmanuel Franck
(
INRIA
, France
)
Scheduled presentations:
-
Non-linear control variate in δf methods using symplectic neural networks
-
Greedy Methods for Neural Network and Application to a Semi-Lagrangian Scheme
-
A Theoretical Analysis of the Neural Approximated Virtual Element Method
-
Lloyd's algorithm and quasi-uniform Voronoi tesselations for particle schemes
-
Progressive Layer Enrichment with Guaranteed Error Reduction in Scientific Machine Learning
-
Acceleration of Bayesien calibration of fast dynamic models via machine learning based surrogate models
