73 citations · 141 across the 26 of their papers we have counts for
4 papers · 1 filter
HyperMagNet: A Magnetic Laplacian based Hypergraph Neural Network
Tatyana Benko, Martin Buck, Ilya Amburg +2
In data science, hypergraphs are natural models for data exhibiting multi-way relations, whereas graphs only capture pairwise. Nonetheless, many proposed hypergraph neural networks…
Randomized Algorithms for Symmetric Nonnegative Matrix Factorization
Koby Hayashi, Sinan G. Aksoy, Grey Ballard +1
Symmetric Nonnegative Matrix Factorization (SymNMF) is a technique in data analysis and machine learning that approximates a symmetric matrix with a product of a nonnegative, low-r…
Skew-Symmetric Adjacency Matrices for Clustering Directed Graphs
Koby Hayashi, Sinan G. Aksoy, Haesun Park
Cut-based directed graph (digraph) clustering often focuses on finding dense within-cluster or sparse between-cluster connections, similar to cut-based undirected graph clustering…
Hypergraph Random Walks, Laplacians, and Clustering
Koby Hayashi, Sinan G. Aksoy, Cheong Hee Park +1
We propose a flexible framework for clustering hypergraph-structured data based on recently proposed random walks utilizing edge-dependent vertex weights. When incorporating edge-d…