Some new methods to build group equivariant non-expansive operators in TDA
Abstract
Group equivariant operators are playing a more and more relevant role in machine learning and topological data analysis. In this paper we present some new results concerning the construction of G-equivariant non-expansive operators (GENEOs) from a space of real-valued bounded continuous functions on a topological space X to itself. The space represents our set of data, while G is a subgroup of the group of all self-homeomorphisms of X, representing the invariance we are interested in.
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