This paper considers structures of systems beyond dyadic (pairwise) interactions and
investigates mathematical modeling of multi-way interactions and connections as hyper …

Background Representing biological networks as graphs is a powerful approach to reveal
underlying patterns, signatures, and critical components from high-throughput biomolecular …

Recent empirical evidence has shown that in many real-world systems, successfully
represented as networks, interactions are not limited to dyads, but often involve three or …

Hypergraphs are a natural and powerful choice for modeling group interactions in the real
world, which are often referred to as higher-order networks. For example, when modeling …

This open access book discusses the theory and methods of hypergraph computation. Many
underlying relationships among data can be represented using graphs, for example in the …

Driven by the importance of relational aspects of data to decision-making, graph algorithms
have been developed, based on simplified pairwise relationships, to solve a variety of …

The acknowledged model for networks of collaborations is the hypergraph model.
Nonetheless when it comes to be visualized hypergraphs are transformed into simple …

Higher-order interactions (HOIs) are ubiquitous in real-world complex systems and
applications. Investigation of deep learning for HOIs, thus, has become a valuable agenda …

With the rapid growth of large online social networks, the ability to analyze large-scale social
structure and behavior has become critically important, and this has led to the development …

A directed hypergraph, which consists of nodes and hyperarcs, is a higher-order data
structure that naturally models directional group interactions (eg, chemical reactions of …