GraphSAGE 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 arXiv William L. Hamilton, Rex Ying, Jure Leskovec 2017