swMATH ID: 33908
Software Authors: William L. Hamilton, Rex Ying, Jure Leskovec
Description: GraphSAGE is a framework for inductive representation learning on large graphs. GraphSAGE is used to generate low-dimensional vector representations for nodes, and is especially useful for graphs that have rich node attribute information.
Homepage: http://snap.stanford.edu/graphsage/
Source Code:  https://github.com/williamleif/GraphSAGE
Keywords: SocialNetworks; arXiv_cs.SI; Machine Learning; arXiv_cs.LG; arXiv_stat.ML; large graphs; GraphSAGE
Related Software: DGL; PyTorch; DeepGCNs; DropEdge; CayleyNets; FastGCN; PairNorm; Eigen-GNN; PointNet; GloVe; Scikit; Adam; node2vec; GraRep; TensorFlow
Cited in: 0 Documents

Standard Articles

1 Publication describing the Software Year
Inductive Representation Learning on Large Graphs
William L. Hamilton, Rex Ying, Jure Leskovec