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Annan Yu

1 paper here

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author position
  • first author1

Across the 1 of 1 paper where every author was matched, so the position is known.

fields
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedArbitrary-Depth Universal Approximation Theorems for Operator Neural Networks

5 citations · 5 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2021★ 5 cited

Arbitrary-Depth Universal Approximation Theorems for Operator Neural Networks

Annan Yu, Chloé Becquey, Diana Halikias +2

The standard Universal Approximation Theorem for operator neural networks (NNs) holds for arbitrary width and bounded depth. Here, we prove that operator NNs of bounded width and a…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.