node-classification

Graph Attention Networks (GAT) vs GCN on the Cora citation dataset using PyTorch Geometric

Graph convolutional networks in plain PyTorch, classifying papers in the Cora, CiteSeer and PubMed citation networks as in Kipf & Welling

GCN图神经网络：理论+实践

datasets for graph learning,···\

Graph mining and node classification project comparing GCN and GraphSAGE on citation network datasets.

Graph Neural Network pipeline for node classification using GCN and GAT with PyTorch Geometric and Optuna.

Project implementing GraphSage for link prediction and node classification. This project reproduces results from a comparative study, exploring embedding methods and evaluating performance on various datasets.

Social Networks, Connectivity, GPS modules

This project applies machine learning techniques to a bibliographic dataset using graph-based approaches with Neo4j and Python. It involves data preprocessing, graph construction, and implementing node classification and link prediction tasks to explore research patterns, collaborations, and topic evolution.

Product Browse Node Classification

EDA, visualization and model training on CrowdSec cyber security data.

This repository contains the implementation of some of the popular Graph Neural Networks (GNNs) using PyTorch Geometric to solve node classification tasks.

Machine learning on company email graph to predict management salary and future connections.

Code for "Vertex-reinforced Random Walk for Network Embedding"

Final assignment of EE226 course in SJTU by Group 12

Official code for the paper "Fixed Aggregation Features Can Rival GNNs" (ICML 2026)

pip install gnn-augment — graph-augmented GNNs (GCN, GraphSAGE, GAT, GIN) for semi-supervised node classification: replace the adjacency with Katz / Rooted PageRank / Graph Gravity / LLM text-embedding views, multi-view training, sparse mode for large graphs (arXiv:1905.09087)

Interactive Marimo WASM app for teaching spectral, node2vec, and GraphSAGE node embeddings with node classification.

This repository provides data splits for the paper "Forward Learning of Graph Neural Networks" (ICLR 2024).

Impact of Layer Depth in GCNs on Node Classification