[DSAA 2018] Autoencoders for Link Prediction and Semi-Supervised Node Classification
Las características principales de vuptran/graph-representation-learning son: Embedding Algorithms.
Las alternativas de código abierto para vuptran/graph-representation-learning incluyen: andompesta/come — Implementation of ComE algorithm. anryyang/hope. benedekrozemberczki/asne — A sparsity aware and memory efficient implementation of "Attributed Social Network Embedding" (TKDE 2018). benedekrozemberczki/attentionwalk — A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018). benedekrozemberczki/bane — A sparsity aware implementation of "Binarized Attributed Network Embedding" (ICDM 2018). aditya-grover/node2vec — This repository provides a reference implementation of node2vec as described in the paper:.
A sparsity aware and memory efficient implementation of "Attributed Social Network Embedding" (TKDE 2018).
This repository provides a reference implementation of node2vec as described in the paper:
