Abstract Summary statistics play an important role in network data analysis. They can
provide us with meaningful insight into the structure of a network. The Randić index is one of …

Causal structure learning, a prominent technique for encoding cause and effect
relationships among variables, through Bayesian Networks (BNs). Merely recovering causal …

A main topic in the study of topological indices is to find bounds of the indices involving
several parameters and/or other indices. In this paper we perform statistical (numerical) and …

We perform a detailed computational study of the recently introduced Sombor indices on
random networks. Specifically, we apply Sombor indices on three models of random …

Let D n be the set of digraphs with n non-isolated vertices. Let D∈ D n and denote by d u+
and du− the outer degree and inner degree, respectively, of the vertex u of D. We define the …

In this paper, we perform analytical and statistical studies of Revan indices on graphs $ G $:
$ R (G)=\sum_ {uv\in E (G)} F (r_u, r_v) $, where $ uv $ denotes the edge of $ G …

Isaac graphs, denoted by Jn is a well known regular graph. Isaac graphs are isomorphic to
hydrogen-suppressed molecular graphs. The invariants considered in this note and applied …

Previous literature on random matrix and network science has traditionally employed
measures derived from nearest-neighbor level spacing distributions to characterize the …

We perform a detailed (computational) scaling study of well-known general indices (the first
and second variable Zagreb indices, M 1 α (G) and M 2 α (G), and the general sum …

A large number of topological indices of the form∑ uv∈ E (G) F (du, dv) are studied in
mathematical chemistry, where uv denotes the edge of the graph G connecting the vertices u …