ASH is a Python software package that allows to represent and analyze dynamic hypergraphs enriched with node attributes. If you use ASH as support to your research consider citing: Failla, A., Citraro ...

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Abstract: Hypergraph community detection reveals both mesoscale structures and functional characteristics of real-life hypergraphs. Although many methods have been developed from diverse perspectives, ...

Abstract: Designing expressive hypergraph kernels that can effectively capture high-order structural information is a fundamental challenge in hypergraph learning. In this paper, we propose a novel ...

Scientists usually use a hypergraph model to predict dynamic behaviors. But the opposite problem is interesting, too. What if researchers can observe the dynamics but don't have access to a reliable ...

In a network, pairs of individual elements, or nodes, connect to each other; those connections can represent a sprawling system with myriad individual links. A hypergraph goes deeper: It gives ...

Hypergraph Agents is a modular, distributed AI workflow framework supporting Elixir, Python, and more. It enables teams to build, orchestrate, and observe complex agentic workflows—ideal for ...

Objective: To address the high-order correlation modeling and fusion challenges between functional and structural brain networks. Method: This paper proposes a hypergraph transformer method for ...

Hypergraphs, which extend traditional graphs by allowing hyperedges to connect multiple nodes, offer a richer representation of complex relationships in fields like social networks, bioinformatics, ...

The “Layer 0” network was created in collaboration with the United States Department of Defense and is now open for commercial Web3 applications. On July 15, Constellation Network opened its ...