Sheaf hypergraph networks

[2309.17116] Sheaf Hypergraph Networks - arXiv

Title:Sheaf Hypergraph Networks ... Abstract:Higher-order relations are widespread in nature, with numerous phenomena involving complex ...

Sheaf Hypergraph Networks | OpenReview

We employ these sheaf hypergraph Laplacians to design two categories of models: Sheaf Hypergraph Neural Networks and Sheaf Hypergraph Convolutional Networks.

Sheaf Hypergraph Networks - OpenReview

We employ these sheaf hypergraph Laplacians to design two categories of models: Sheaf Hypergraph Neural Networks and Sheaf Hyper- graph Convolutional Networks.

Code for Sheaf Hypergraph Networks paper - GitHub

Code for Sheaf Hypergraph Networks paper. Contribute to IuliaDuta/sheaf_hypergraph_networks development by creating an account on GitHub.

Appendix: Sheaf Hypergraph Networks - NIPS papers

Differently, our Sheaf Hypergraph. Networks aim to reduce the discrepancy between the neighbouring representations in the hyperedge space (right). This has ...

Sheaf hypergraph networks | Proceedings of the 37th International ...

Current approaches typically represent these interactions using hypergraphs. We enhance this representation by introducing cellular sheaves for ...

Sheaf Hypergraph Networks - arXiv

We employ these sheaf hypergraph Laplacians to design two categories of models: Sheaf Hypergraph Neural Networks and Sheaf Hyper- graph ...

SPHINX: Structural Prediction using Hypergraph Inference Network

We employ these sheaf hypergraph Laplacians to design two categories of models: Sheaf Hypergraph Neural Networks and Sheaf Hypergraph Convolutional Networks.

Sheaf-based Positional Encodings for Graph Neural Networks

We present two methodologies for creating sheaf-based positional encodings, showcasing their efficacy in node and graph tasks.

A Sheaf-based Approach to Graph Neural Networks - YouTube

The multitude of applications where data is attached to spaces with non-Euclidean structure has driven the rise of the field of Geometric ...

Iulia Duta on X: " Very happy to announce that Sheaf Hypergraph ...

Very happy to announce that Sheaf Hypergraph Networks got accepted to #NeurIPS2023. Many thanks to my collaborators @glcssr @fabreetseo ...

SHEAF NEURAL NETWORKS WITH CONNECTION LAPLACIANS

A Sheaf Neural Network (SNN) is a type of Graph Neural Network (GNN) that operates on a sheaf, an object that equips a graph with vector spaces over its nodes.

Cristian Bodnar on X: "Very exciting work bringing Sheaf Neural ...

Very happy to announce that Sheaf Hypergraph Networks got accepted to #NeurIPS2023. Many thanks to my collaborators @glcssr @fabreetseo ...

A gentle introduction to sheaves on graphs - Jakob Hansen

Let F be a sheaf on a graph G and G a sheaf on a graph H. The ... Diffusion on graphs is also used to specify consensus dynamics on networks specifi-.

[PDF] Equivariant Hypergraph Diffusion Neural Operators

Sheaf Hypergraph Networks · Iulia DutaGiulia CassaraFabrizio SilvestriPietro Lió. Mathematics, Computer Science. NeurIPS. 2023. TLDR. This work introduces ...

‪Giulia Cassarà‬ - ‪Google Scholar‬

Sheaf hypergraph networks. I Duta, G Cassarà, F Silvestri, P Liò. Advances in ... Sheaf neural networks for graph-based recommender systems. A Purificato ...

(PDF) Heterogeneous Sheaf Neural Networks - ResearchGate

Standard Graph Neural Networks (GNNs) struggle to process heterogeneous data due to oversmoothing. Instead, current approaches have focused on ...

Sheaves for AI: Graph Representation Learning through Sheaf Theory

"Network embedding as matrix factorization: Unifying deepwalk, line, pte, and node2vec." Proceedings of the eleventh ACM international conference on web search ...

Sheaf Neural Networks - Thomas Gebhart

The sheaf Laplacian and associated matrices provide an extended version of the diffusion operation in graph convolutional networks, providing a proper ...

[PDF] Preventing Over-Smoothing for Hypergraph Neural Networks

Sheaf Hypergraph Networks · Iulia DutaGiulia CassaraFabrizio SilvestriPietro Lió. Mathematics, Computer Science. NeurIPS. 2023. TLDR. This work introduces ...