Backtrackless walks on a graph

Abstract: The aim of this talk is to explore the use and applications of backtrackless walks on a graph. We will discuss how the backtrackless walks and the coefficients of the reciprocal of the Ihara zeta function, which are related to the frequencies of prime cycles in the graph, can be used to implement graph kernels. We will further present explicit methods for computing the eigensystem of the edge-based Laplacian of a graph. This reveals a connection between the eigenfunctions of the edge-based Laplacian and both the classical random walk and the backtrackless random walk on a graph. The definition of edge-based Laplacian allows us to define and implement more complex partial differential equations on graphs such as the second order wave equation.

Computer scienceMathematicsPhysics

Audience: researchers in the topic

Data Science and Computational Statistics Seminar