Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

B站GNN教程资料

Comparative Analysis of Graph Neural Networks for Node Regression on Wiki-Squirrel dataset (bachelor's Research Project)

This repository presents and compares HeterSUMGraph and variants using GATConv, GATv2Conv and a combination of HeterSUMGraph and SummaRuNNer (using HeterSUMGraph as a sentence encoder).

Empirical Research over the possible advantages of pretraining a Graph Neural Network for Classification by using Link Prediction. We used GCN, GAT and GraphSAGE with minibatch generation. Done for the Learning From Networks course taught by professor Fabio Vandin at the University of Padova

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

This repository consists from scratch implementation of GCN, GAT and GATv2.

A web application for extractive summarization

This repository presents and compares HeterSUMGraph and variants doing extractive summarization, named entity recognition or both. HeterSUMGraph and variants use GATv2Conv (from torch_geometric).