Hypergraphs, encoding structured interactions among any number of system units, have
recently proven a successful tool to describe many real-world biological and social …

Many networks can be characterized by the presence of communities, which are groups of
units that are closely linked. Identifying these communities can be crucial for understanding …

A wide variety of complex systems are characterized by interactions of different types
involving varying numbers of units. Multiplex hypergraphs serve as a tool to describe such …

We consider the community detection problem in a sparse-uniform hypergraph, assuming
that is generated according to the Hypergraph Stochastic Block Model (HSBM). We prove …

In recent years hypergraphs have emerged as a powerful tool to study systems with
multibody interactions which cannot be trivially reduced to pairs. While highly structured …

Abstract The Artificial Benchmark for Community Detection (ABCD) graph is a recently
introduced random graph model with community structure and power-law distribution for …

The scattering transform is a multilayered, wavelet-based transform initially introduced as a
model of convolutional neural networks (CNNs) that has played a foundational role in our …

Many complex systems often contain interactions between more than two nodes, known as
higher-order interactions, which can change the structure of these systems in significant …

Consider the community detection problem in random hypergraphs under the non-uniform
hypergraph stochastic block model (HSBM), where each hyperedge appears independently …

The hypergraph community detection problem seeks to identify groups of related vertices in
hypergraph data. We propose an information-theoretic hypergraph community detection …