arXiv Machine Learning July 16, 2026 By Janek G\"odeke, Pascal Fernsel

New universal operator approximation theorem for encoder-decoder architectures

Read the original on arXiv Machine Learning →

arXiv:2503. 24092v2 Announce Type: replace-cross Abstract: Motivated by the rapidly growing field of mathematics for operator approximation with neural networks, we present a novel universal operator approximation theorem for broad classes of encoder-decoder architectures and a wide range of input and output spaces.

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