139 citations · 555 across the 26 of their papers we have counts for
3 papers · 1 filter
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems
Derick Nganyu Tanyu, Jianfeng Ning, Tom Freudenberg +4
Recent years have witnessed a growth in mathematics for deep learning--which seeks a deeper understanding of the concepts of deep learning with mathematics and explores how to make…
SELTO: Sample-Efficient Learned Topology Optimization
Sören Dittmer, David Erzmann, Henrik Harms +1
Recent developments in Deep Learning (DL) suggest a vast potential for Topology Optimization (TO). However, while there are some promising attempts, the subfield still lacks a firm…
PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization
Fabian Altekrüger, Alexander Denker, Paul Hagemann +3
Learning neural networks using only few available information is an important ongoing research topic with tremendous potential for applications. In this paper, we introduce a power…