A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide
Higher-order interactions (HOIs) are ubiquitous in real-world complex systems and
applications, and thus investigation of deep learning for HOIs has become a valuable …
applications, and thus investigation of deep learning for HOIs has become a valuable …
Hypeboy: Generative self-supervised representation learning on hypergraphs
Hypergraphs are marked by complex topology, expressing higher-order interactions among
multiple nodes with hyperedges, and better capturing the topology is essential for effective …
multiple nodes with hyperedges, and better capturing the topology is essential for effective …
Higher-order networks representation and learning: A survey
H Tian, R Zafarani - arXiv preprint arXiv:2402.19414, 2024 - arxiv.org
Network data has become widespread, larger, and more complex over the years. Traditional
network data is dyadic, capturing the relations among pairs of entities. With the need to …
network data is dyadic, capturing the relations among pairs of entities. With the need to …
Ada-HGNN: Adaptive Sampling for Scalable Hypergraph Neural Networks
Hypergraphs serve as an effective model for depicting complex connections in various real-
world scenarios, from social to biological networks. The development of Hypergraph Neural …
world scenarios, from social to biological networks. The development of Hypergraph Neural …
HypergraphRepository: A Community-Driven and Interactive Hypernetwork Data Collection
Hypergraph research has been thriving over the past few years, with a growing interest in a
plethora of domains. Despite this remarkable surge, the lack of a comprehensive platform for …
plethora of domains. Despite this remarkable surge, the lack of a comprehensive platform for …