Network Shapes Repository is a research data collection from the Data Lab, EECS Department, Syracuse University. For each network we generate shapes using multiple sampling methods (Random Edge, Random Node, Random Walk), embedding methods (Kronecker Points, Graph2Vec, Spectral Points), and fitting methods (Convex Hull, Cuboid, Sphere). All shape data and generation code are freely available.

110
Datasets
13
Categories
3
Sampling Methods
3
Embeddings
3
Shape Types
Datasets Click column headers to sort
Graph Category Vertices Edges
📊 Shape generation code available on GitHub: shengminjin/NetworkShapesDataset  |  Spectral embedding: shengminjin/EstimateSpectralMoments