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The necessity of depth for artificial neural networks to approximate certain classes of smooth bounded functions without the curse of dimensionality Gonon, L.; Graeber, R.; Jentzen, A. (2023) In: arXiv.org:2212.13111. Research article in digital collection \| Preprint \| submitted / under review
Deep neural network approximation theory for high-dimensional functions Beneventano P, Cheridito P, Graeber R, Jentzen A, Kuckuck B (2021) In: Sampling Theory in Signal and Image Processing, 0. Research article (journal) \| Peer reviewed \| accepted / in press (not yet published)