[01104] Generation of $hp$-FEM Massive Databases for Deep Learning Inversion
Session Time & Room : 2D (Aug.22, 15:30-17:10) @E506
Type : Contributed Talk
Abstract : Deep Neural Networks are employed in many geophysical applications to characterize the Earth’s subsurface. However, they often need to solve hundreds of thousands of complex and expensive forward problems to produce the training dataset.
This work presents a robust approach to producing massive databases at a reduced computational cost. In particular, we build a single $hp$-adapted mesh that accurately solves many FEM problems for any combination of parameters within a given range.
