Ecosystem functioning depends on multiple successful interactions, many supported by
individual movements. The degree to which the landscape allows these interactions to take …

This paper develops an approximation to the (effective) $ p $-resistance and applies it to
multi-class clustering. Spectral methods based on the graph Laplacian and its …

In this paper we propose a new method, Return Random Walk, for link prediction to infer
new intra-class edges while minimizing the amount of inter-class noise, and we show how to …

This work extends the randomized shortest paths (RSP) model by investigating the net flow
RSP and adding capacity constraints on edge flows. The standard RSP is a model of …

This work elaborates on the important problem of (1) designing optimal randomized routing
policies for reaching a target node t from a source note s on a weighted directed graph G …

Randomized shortest paths (RSPs) are tool developed in recent years for different graph
and network analysis applications, such as modelling movement or flow in networks. In …

The recently developed bag-of-paths (BoP) framework consists in setting a Gibbs–
Boltzmann distribution on all feasible paths of a graph. This probability distribution favors …

The fields of effective resistance and optimal transport on graphs are filled with rich
connections to combinatorics, geometry, machine learning, and beyond. In this article we put …

The emergence of networks and network data in different forms in the near past has given
rise to development of new data analysis methods with a shift in focus from vector spaces to …

We explain Poisson learning on graph-based semi-supervised learning to see if it could
avoid the problem of global information loss problem as Laplace-based learning methods …