shenxiaocam/Deep-network-embedding-for-graph-representation-learning-in-signed-networks

Deep network embedding for graph representation learning in signed networks

The main features of shenxiaocam/deep-network-embedding-for-graph-representation-learning-in-signed-networks are: Embedding Algorithms.

Open-source alternatives to shenxiaocam/deep-network-embedding-for-graph-representation-learning-in-signed-networks include: 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:.