Hodge-Compositional Edge Gaussian Processes

arXiv:2310.19450v3 Announce Type: replace-cross
Abstract: We propose principled Gaussian processes (GPs) for modeling functions defined over the edge set of a simplicial 2-complex, a structure similar to a graph in which edges may form triangular faces. This approach is intended for learning flow-type data on networks where edge flows can be characterized by the discrete divergence and curl. Drawing upon the Hodge decomposition, we first develop classes of divergence-free and curl-free edge GPs, suitable for various applications. We then combine …

abstract arxiv cs.lg data divergence edge flow form functions gaussian processes gps graph modeling networks processes set stat.ml the edge type