Results 151 to 160 of about 56,162 (272)
Hypergraph-Mlp: Learning on Hypergraphs Without Message Passing
Hypergraphs are vital in modelling data with higher-order relations containing more than two entities, gaining prominence in machine learning and signal processing. Many hypergraph neural networks leverage message passing over hypergraph structures to enhance node representation learning, yielding impressive performances in tasks like hypergraph node ...
Tang, B, Chen, S, Dong, X
openaire +3 more sources
Multimodal Emotion Recognition in Conversation Based on Hypergraphs [PDF]
Jiaze Li +3 more
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Minimum-Weight Edge Discriminators in Hypergraphs [PDF]
Bhaswar B. Bhattacharya +2 more
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Connected components in networks with higher-order interactions
We address the problem of defining connected components in hypergraphs, which are models for systems with higher-order interactions. For graphs with dyadic interactions, connected components are defined in terms of paths connecting nodes along the graph.
Gyeong-Gyun Ha +2 more
doaj +1 more source
Hypergraphes de Petersen! Hypergraphes de Moore?
RésuméOn étudie ici des sous structures des plan projectifs finis Pg(2,n) oú n est impair. Dans ceux-ci les (n + 1)-arcs induisent une décomposition canonique.Soit E l'ensemble des points, D celui des droites, appelons X l'ensemble des points d'un (n+1)-arc.
openaire +1 more source
Extending Graph-Based LP Techniques for Enhanced Insights Into Complex Hypergraph Networks
Many real-world problems can be modelled in the form of complex networks. Social networks such as research collaboration networks and facebook, biological neural networks such as human brains, biomedical networks such as drug-target interactions and ...
Y. V. Nandini +4 more
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A Note on a Broken-Cycle Theorem for Hypergraphs
Whitney’s Broken-cycle Theorem states the chromatic polynomial of a graph as a sum over special edge subsets.
Trinks Martin
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Entropy-based models to randomise real-world hypergraphs
Network theory has often disregarded many-body relationships, solely focusing on pairwise interactions: neglecting them, however, can lead to misleading representations of complex systems.
Fabio Saracco +3 more
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