mlsanityData to 7 Oct 2026

Hypergraph: A Unified and Uniform Definition with Application to Chemical Hypergraph and More

arXiv 2405.12235 ↗First posted 14 May 2024cs.LG q-bio.QMcited by 3

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Abstract (arXiv)

The conventional definition of hypergraph has two major issues: (1) there is not a standard definition of directed hypergraph and (2) there is not a formal definition of nested hypergraph. To resolve these issues, we propose a new definition of hypergraph that unifies the concepts of undirected, directed and nested hypergraphs, and that is uniform in using hyperedge as a single construct for representing high-order correlations among things, i.e., nodes and hyperedges. Specifically, we define a hyperedge to be a simple hyperedge, a nesting hyperedge, or a directed hyperedge. With this new definition, a hypergraph is nested if it has nesting hyperedge(s), and is directed if it has directed hyperedge(s). Otherwise, a hypergraph is a simple hypergraph. The uniformity and power of this new definition, with visualization, should facilitate the use of hypergraph for representing (hierarchical) high-order correlations in general and chemical systems in particular. Graph has been widely used as a mathematical structure for machine learning on molecular structures and 3D molecular geometries. However, graph has a major limitation: it can represent only pairwise correlations between nodes. Hypergraph extends graph with high-order correlations among nodes. This extension is significant or essential for machine learning on chemical systems. For molecules, this is significant as it allows the direct, explicit representation of multicenter bonds and molecular substructures. For chemical reactions, this is essential since most chemical reactions involve multiple participants. We propose the use of chemical hypergraph, a multilevel hypergraph with simple, nesting and directed hyperedges, as a single mathematical structure for representing chemical systems. We apply the new definition of hypergraph to chemical hypergraph and, as simplified versions, molecular hypergraph and chemical reaction hypergraph.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 14 May 2024.

Builds on

5 of 11 references.

References · 5

  1. 2022A Survey on Hyperlink Predictioncited by 9
  2. 2019Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Axcited by 6
  3. 2019Deep Learning for Molecular Graphs with Tiered Graph Autoencoders and Graph Predictioncited by 2
  4. 2023Clinical Note Owns its Hierarchy: Multi-Level Hypergraph Neural Networks for Patient-Level Representation Learningcited by 2
  5. 2022Distance-Geometric Graph Attention Network (DG-GAT) for 3D Molecular Geometrycited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 1.

3 papers.