Geist, Moritz; Petersen, Philipp; Raslan, Mones; Schneider, Reinhold; Kutyniok, Gitta Astrid Hildegard (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-05)
We perform a comprehensive numerical study of the effect of approximation-theoretical
results for neural networks on practical learning problems in the context of numerical analysis. As the underlying model, we study the machine-learning-based solution of parametric
partial differential equations. Here, approximation theory for fully-connected neural networks
predicts that the performance of the ...