5 citations · 12 across the 12 of their papers we have counts for
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cs.LG2023★ 3 cited
Universal approximation property of Banach space-valued random feature models including random neural networks
Ariel Neufeld, Philipp Schmocker
We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel approximation. By randomly initi…
stat.ML2023★ 2 cited
Global universal approximation of functional input maps on weighted spaces
Christa Cuchiero, Philipp Schmocker, Josef Teichmann
We introduce so-called functional input neural networks defined on a possibly infinite dimensional weighted space with values also in a possibly infinite dimensional output space.…