GitHub topics: deep-graph-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.
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PetarV-/DGI
Deep Graph Infomax (https://arxiv.org/abs/1809.10341)
Language: Python - Size: 136 KB - Last synced at: about 7 hours ago - Pushed at: over 2 years ago - Stars: 641 - Forks: 137

vla6/Blog_gnn_naics
Exploring categorical features with various encodings and models
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rutu-sh/player-compatibality-and-win-pred-in-dota2-using-graph-neural-networks
A GNN based approach to model player compatibility in Multiplayer Online Battle Arena (MOBA) games like Dota2.
Size: 771 KB - Last synced at: about 1 month ago - Pushed at: almost 2 years ago - Stars: 4 - Forks: 0

alphagov/govuk-entity-personalisation 📦
Using entities from NER on GOV.UK content to power personalisation.
Language: Jupyter Notebook - Size: 1.07 MB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 4
