Hypergraphs are hot: they're starting to become a more frequent topic of discussion, sometimes even sketched as successors to knowledge graphs and graph-structured data generally. Kurt Cagle's recent ...

Abstract: We revisit semi-supervised learning on hypergraphs. Same as previous approaches, our method uses a convex program whose objective function is not everywhere differentiable. We exploit the ...

The topic to be covered in this article is an interesting concept called "Hypergraphs". It would be covered in multiple articles across the series (not necessarily in ordered manner). This first ...

Abstract: The technique of equality saturation, which equips graphs with an equivalence relation, has proven effective for program optimisation. We give a categorical semantics to these structures, ...

Over the last three decades, the introduction of various types and models of complex networks to represent the interactions between different parts of a complex system has become a widely recognized ...

Hyperbase is a foundational library for working with Semantic Hypergraphs (SH), which make it possible to represent a natural language sentence such as "Einstein first published the theory of ...

Network scientists have shown that there is great value in studying pairwise interactions between components in a system. From a linear algebra point of view, this involves defining and evaluating ...

Formalizing progress on Epoch AI's FrontierMath open problem on hypergraphs. This repository formalizes lower bounds for the extremal hypergraph function $H(n ...