Network community detection via neural embeddings
Recent advances in machine learning research have produced powerful neural graph
embedding methods, which learn useful, low-dimensional vector representations of network …
embedding methods, which learn useful, low-dimensional vector representations of network …
Theory of percolation on hypergraphs
G Bianconi, SN Dorogovtsev - Physical Review E, 2024 - APS
Hypergraphs capture the higher-order interactions in complex systems and always admit a
factor graph representation, consisting of a bipartite network of nodes and hyperedges. As …
factor graph representation, consisting of a bipartite network of nodes and hyperedges. As …
Nature of hypergraph -core percolation problems
G Bianconi, SN Dorogovtsev - Physical Review E, 2024 - APS
Hypergraphs are higher-order networks that capture the interactions between two or more
nodes. Hypergraphs can always be represented by factor graphs, ie, bipartite networks …
nodes. Hypergraphs can always be represented by factor graphs, ie, bipartite networks …
General theory for extended-range percolation on simple and multiplex networks
Extended-range percolation is a robust percolation process that has relevance for quantum
communication problems. In extended-range percolation nodes can be trusted or untrusted …
communication problems. In extended-range percolation nodes can be trusted or untrusted …
Robustness of hypergraph under attack with limited information based on percolation theory
Y Duan, J Huang, H Deng, X Ni - Chaos, Solitons & Fractals, 2024 - Elsevier
Hypergraphs serve as a representative form to display higher-order interactions that persist
in the community structure of ecological and social systems. A significant characteristic of …
in the community structure of ecological and social systems. A significant characteristic of …
A message-passing approach to obtain the trace of matrix functions with applications to network analysis
GE Castro Guzman, PF Stadler, A Fujita - Numerical Algorithms, 2025 - Springer
Graphs have become a commonly used model to study technological, biological, and social
systems. Various methods have been proposed to measure graphs' structural and …
systems. Various methods have been proposed to measure graphs' structural and …
An approximation for return time distributions of random walks on sparse networks
E Hormann, R Lambiotte, GT Cantwell - arXiv preprint arXiv:2405.20166, 2024 - arxiv.org
We propose an approximation for the first return time distribution of random walks on
undirected networks. We combine a message-passing solution with a mean-field …
undirected networks. We combine a message-passing solution with a mean-field …