GitHub topics: deep-infomax
mahnoorsheikh16/Node-Classification-with-Graph-Neural-Networks
Evaluation of multiple graph neural network models—GCN, GAT, GraphSAGE, MPNN and DGI—for node classification on graph-structured data. Preprocessing includes feature normalization and adjacency-matrix regularization, and an ensemble of model predictions boosts performance. The best ensemble achieves 83.47% test accuracy.
Language: Jupyter Notebook - Size: 285 KB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 1 - Forks: 0

caojiangxia/BiGI
[WSDM 2021]Bipartite Graph Embedding via Mutual Information Maximization
Language: Python - Size: 1.89 MB - Last synced at: 18 days ago - Pushed at: almost 4 years ago - Stars: 76 - Forks: 13

rcalland/deep-INFOMAX
Chainer implementation of deep-INFOMAX
Language: Python - Size: 114 KB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 34 - Forks: 12

p3i0t/SDIM_logits
Deriving Generative Classifier From Any Given Discriminative Classifier
Language: Python - Size: 74.4 MB - Last synced at: 5 days ago - Pushed at: about 5 years ago - Stars: 2 - Forks: 1
