PyTorch implementation of GNN models
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Updated
May 21, 2024 - Jupyter Notebook
PyTorch implementation of GNN models
repo for learning graph neural network
This repo contains Pytorch-Lightning implementations of GCN and GraphSAGE for Node Classification and Link Prediction (as a way for Recommendation System) on the Cora dataset and CUHKSZ-AG dataset.
B站GNN教程资料
A Nextflow pipeline demonstrating how to train graph neural networks for gene regulatory network reconstruction using DREAM5 data.
GNN training in kubeflow.
Dist-DGL running on wsl2, minikube with single machine
DGL Implementation of "Efficient Sampling Techniques for Embedding Large Graphs". KCC 2022
Official DGL Implementation of "Distributed Graph Data Augmentation Technique for Graph Neural Network". KSC 2023
Graph Neural Network predicting the chemical composition of organism across the tree of life.
Comparative Analysis of Graph Neural Networks for Node Regression on Wiki-Squirrel dataset (bachelor's Research Project)
Graph Neural Networks for Expertise Classification on Stack Overflow
learning station embedding
Django Application of a Book Recommendation Graph Network (GraphSAGE)
Prediction of abnormal return of selected publically trading pharma companies using NLP techniques and tools; special focus on graph-based representation of transcripts of a conversation.
A distributed graph deep learning framework.
Fraud Detection using various GNN models
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