- [PDF] MSGNN🔍
- A Survey on Hypergraph Neural Networks🔍
- A spectral graph convolution for signed directed graphs via ...🔍
- Dynamic weighted hypergraph convolutional network for brain ...🔍
- Dynamic Weighted Hypergraph Convolutional Network for Brain ...🔍
- Heterogeneous Graph Convolutional Neural Network via Hodge ...🔍
- Graph Neural Networks Designed for Different Graph Types🔍
- Hypergraph based learning method🔍
A Magnetic Laplacian based Hypergraph Neural Network
[PDF] MSGNN: A Spectral Graph Neural Network Based on a Novel ...
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian ... HyperMagNet: A Magnetic Laplacian based Hypergraph Neural Network · Tatyana ...
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By ...
Hypermagnet: A magnetic laplacian based hypergraph neural network. arXiv preprint arXiv:2402.09676 (2024). Austin R Benson Ravi Kumar and Andrew Tomkins ...
A spectral graph convolution for signed directed graphs via ...
In other words, the traditional graph Laplacian and the Laplacian of MagNet are special cases of ours. ... Msgnn: A spectral graph neural network based on a novel ...
Dynamic weighted hypergraph convolutional network for brain ...
Unlike existing graph and hypergraph based neural network ... Examining brain maturation during adolescence using graph Laplacian learning based Fourier transform.
Dynamic Weighted Hypergraph Convolutional Network for Brain ...
Unlike existing graph and hypergraph based neural network ... Examining brain maturation during adolescence using graph laplacian learning based ...
Heterogeneous Graph Convolutional Neural Network via Hodge ...
a spatial pooling operator based on graph topology. 2 Methods. This study designs a heterogeneous graph convolutional neural network via the. Hodge-Laplacian ...
Graph Neural Networks Designed for Different Graph Types: A Survey
convolution using a complex-valued Hermitian matrix, called magnetic Laplacian, instead of a symmetric and ... Hypergraph neural network for skeleton-based action ...
Hypergraph based learning method: Embedding, Clustering, and ...
Keywords : graph, hypergraph, Laplacian, semi-supervised learning method, clustering, em- beddings, neural network. iii. Page 11. Table of ...
Hypergraph Computation - OAPEN Library
self-attention-based hypergraph neural network (Hyper-SAGNN). By mapping the ... Based on the hypergraph Laplacian and the Chebyshev formula, Feng et al.
Ilya Amburg - Google 学术搜索 - Google Scholar
2015. Hypermagnet: A magnetic laplacian based hypergraph neural network. T Benko, M Buck, I Amburg, SJ Young, SG Aksoy. arXiv preprint arXiv:2402.09676, 2024. 2 ...
HpLapGCN: Hypergraph p-Laplacian Graph Convolutional Networks
In another work, a neoteric attitude was developed on the basis of hypergraph to find the optimal property subset along with arithmetic residue-based neural ...
Hypergraph Structure Learning for Hypergraph Neural Networks
In the second stage, the hypergraph structures are adjusted at a fine-grained level via incident node sampling. Potential implicit connec- tions are discovered ...
Michael A. Perlmutter - Publications - Google Sites
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian - Joint Work with Y. He, G. Reinert, M. Cucuringu - Learning on Graphs ...
A Multi-Modal Hypergraph Neural Network via Parametric Filtering ...
In the residual connection, the previous node features are embedded by the hypergraph Laplacian operator. ... In hypergraph based semi-supervised learning, Z_$\ ...
Android Malware Detection Based on Hypergraph Neural Networks
HyperGCN [26] simplifies the hypergraph by defining a non-linear Laplacian matrix that generates only one simple edge for each hyperedge, i.e., taking the two ...
A Survey on Hypergraph Neural Networks: An In-Depth and Step-by ...
Hypermagnet: A magnetic laplacian based hypergraph neural network. arXiv preprint arXiv:2402.09676 (2024). [10] Austin R Benson, Ravi Kumar ...
Spectral graph theory relates properties of a graph to a spectrum, i.e., eigenvalues, and eigenvectors of matrices associated with the graph, such as its ...
HyperMagNet: A Magnetic Laplacian based Hypergraph Neural ...
We propose an alternative approach to hypergraph neural networks in which the hypergraph is represented as a non-reversible Markov chain. We use this Markov ...
Hodge-Laplacian of Brain Networks and Its Application to Modeling ...
... magnetic resonance images. New statistical ... zation of brain networks across multiple resolutions is crucial. Often graph theory based ...
NHP: Neural Hypergraph Link Prediction - MALL Lab @ IISc
Nonlinear Laplacian for Digraphs and Its Applications to. Network Analysis. ... Hyper-{SAGNN}: a self-attention based graph neural network for hypergraphs.