The article "Diversity of EML-type operators" discusses the EML operator, which can evaluate standard explicit purely transcendental elementary functions, and notes that while most research has focused on the binary EML, many similar variants exist. It enumerates and classifies these variants, clarifies common misconceptions, and proposes a M"obius layer that replaces matrix operations with rational functions. The paper also showcases the activation function eml(x,1/x), enabling separate recovery of exp(x) and ln(x) and thus evaluation of all elementary functions within a rational neural‑network generalization.
By Andrzej Odrzywo{\l}ek
arXiv:2402. 00094v3 Announce Type: replace-cross Abstract: We introduce a new class of deep neural networks (DNNs) with multilayered tree-like architectures.
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arXiv:2606. 20325v1 Announce Type: new Abstract: Classical approximation theorems ask for a new neural network whenever the target accuracy is improved.
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arXiv:2606. 08727v1 Announce Type: cross Abstract: Many classically studied function classes are known to be approximated optimally by superpositional methods, i.
By Dennis Elbr\"achter, Philipp Petersen