vgae

This repository implements variational graph auto encoder by Thomas Kipf.

gcn for prediction of protein interactions，图卷积用于蛋白质相互作用。

This repository shows an implementation of the VGAE based model with PyTorch.

Official Repository for different models based on MultiHead VGAEs.

Graph Neural Network for Disease-Gene Link Prediction

Graph-based Contrastive Learning enable Fast Single-Cell Embedding

APPNP,ARGO,ARMA,BGNN,BGRL,CAPSULE,CAREGNN,CLUSTER_GCN,COMPGCN,CORRECT_AND_SMOOTH,DAGNN,DEEPERGNN,DEEPWALK,DGI,DGMG,DIFFPOOL,DIMENET,DTGRNN,EEG-GCNN,EGES,EVOLVEGCN,GAS,GAT,GATNE-T,GATV2,GCMC,GCN,GENIEPATH,GGNN,GIN,GNN_EXPLAINER,GRACE,GRAND,GRAPH_MATCHING,GRAPHSAINT,GRAPHSAGE,GRAPHSIM,GRAPHWRITER,GXN,HAN,HARDGAT,HARDGAT,HGP_SL,HGT,HILANDER,INFOGRAPH

A comprehensive bridge impact analysis system combining heterogeneous graph neural networks (HGNN) for closure-impact prediction with graph autoencoders (GAE/VGAE/HetVGAE) for unsupervised bridge similarity learning. This extends the system with heterogeneous graph variational autoencoders for metapath-based bridge classification.

Three approaches to learned graph generation compared side by side: variational autoencoder (VGAE), autoregressive RNN, and denoising diffusion.

Repositório de TCC com pipeline completo para experimentos com GNNs: geração de embeddings (GAE/VGAE), avaliação com múltiplos classificadores e ambiente reproduzível via Dev Containers.