Critical nodes in networks are extremely vulnerable to malicious attacks to trigger negative
cascading events such as the spread of misinformation and diseases. Therefore, effective …

The total effective resistance, also called the Kirchhoff index, provides a robustness measure
for a graph G. We consider two optimization problems of adding k new edges to G such that …

Effective resistance is a distance between vertices of a graph that is both theoretically
interesting and useful in applications. We study a variant of effective resistance called the …

We study second-order consensus dynamics with random additive disturbances. To quantify
the robustness of these networks, we investigate three different performance measures: the …

The spectral radius of the non-backtracking matrix for an undirected graph plays an
important role in various dynamic processes running on the graph. For example, its …

The biharmonic distance (BD) is a fundamental metric that measures the distance of two
nodes in a graph. It has found applications in network coherence, machine learning, and …

For random walks on graph with vertices and edges, the mean hitting time from a vertex
chosen from the stationary distribution to vertex measures the importance for, while the …

Centrality metrics are one of the most fundamental tools in social network analysis and
network science, and various measures for evaluating node importance metrics have been …

Edge centrality has found wide applications in various aspects. Many edge centrality metrics
have been proposed, but the crucial issue that how good the discriminating power of a …

The grounded Laplacian matrix L− S of a graph G=(V, E) with n=| V| nodes and m=| E| edges
is a (n− s)×(n− s) submatrix of its Laplacian matrix L, obtained from L by deleting rows and …