Distances for Markov Chains, and Their Differentiation

arXiv:2302.08621v2 Announce Type: replace
Abstract: (Directed) graphs with node attributes are a common type of data in various applications and there is a vast literature on developing metrics and efficient algorithms for comparing them. Recently, in the graph learning and optimization communities, a range of new approaches have been developed for comparing graphs with node attributes, leveraging ideas such as the Optimal Transport (OT) and the Weisfeiler-Lehman (WL) graph isomorphism test. Two state-of-the-art representatives are the OTC distance proposed in …

abstract algorithms applications arxiv communities cs.lg data differentiation graph graph learning graphs literature markov metrics node optimization them type vast