Shypd.aiThe largest open index of AI toolsHGNN is an Open Source & Models tool that provides Hypergraph Neural Networks for data representation learning. It supports various correlation structures and offers visualization capabilities for complex data.
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HGNN (Hypergraph Neural Networks) is an open-source framework designed for data representation learning, particularly effective with multi-modal data. It incorporates high-order data correlation into a hypergraph structure, offering a more flexible approach to data modeling than traditional graph-based methods. The tool features a hyperedge convolution operation to efficiently handle data correlation during representation learning. HGNN is capable of learning hidden layer representations by considering complex data structures, making it a general framework for diverse data correlations. The repository includes code and data for training Hypergraph Neural Networks for node classification on datasets like ModelNet40 and NTU2012, utilizing features extracted by MVCNN and GVCNN.
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