Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots.

ABSTRACT: Most problems within and beyond the scientific domain can be framed into one of the following three levels of complexity of function approximation. Type 1: Approximate an unknown function given input/output data. Type 2: Consider a collection of variables and functions, some of which are unknown, indexed by the nodes and hyperedges of a hypergraph (a generalized graph where edges can connect more than two vertices). Given partial observations of the variables of the hypergraph (satisfying the functional dependencies imposed by its structure), approximate all the unobserved variables and unknown functions. Type 3: Expanding on Type 2, if the hypergraph structure itself is unknown, use partial observations of the variables of the hypergraph to discover its structure and approximate its unkno

SUBMITTER: Bourdais T 

PROVIDER: S-EPMC11317615 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature