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Code of MSTFGRN (Spatial-Temporal/ Traffic data forecasting)
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).
The released code for the paper: ''Embracing Long-range Dependency in Graph Classification by Stacking Graph Neural Network" in WebConf 2023
Developing multiple ML Classifiers using SVM, PCA, Decision Tree, Random Forest, GMM & MLP Models for detecting Faults in Power Systems and comparing their accuracies & performances.
A sample power system was modeled using MATLAB Simulink and all six types of faults were introduced into the transmission line of the power system. An ML classifier using 8 types model was implemen…
Master Thesis: Optimal Power Flow in Power Systems using Graph Neural Networks
GNN for k-contingency screening in power system networks.
图神经网络、图卷积网络、图注意力网络、图自编码网络、时空图神经网络等论文合集。
GNN方法和模型的Pytorch实现。Pytorch implementation of GNN.
Revisiting Graph Neural Networks for Vulnerability Detection (ICSE 2022) (Pytorch)
Some GNNs are implemented using PyG for node classification tasks, including: GCN, GraphSAGE, SGC, GAT, R-GCN and HAN (Heterogeneous Graph Attention Network), which will continue to be updated in t…
[ICML 2019] Circuit-GNN: Graph Neural Networks for Distributed Circuit Design http://circuit-gnn.csail.mit.edu/
Traffic Flow Prediction with Vehicle Trajectories
Supervised community detection with line graph neural networks
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.
[TNNLS 2022] Code for "Learning Disentangled Graph Convolutional Networks Locally and Globally"