GraphGallery is a gallery for benchmarking Graph Neural Networks

Transform geospatial relations into graph representations designed for spatial analysis and Graph Neural Networks (GNNs).

This is a PyTorch implementation of the GeniePath model in <GeniePath: Graph Neural Networks with Adaptive Receptive Paths> (https://arxiv.org/abs/1802.00910)

A Pytorch Implementation of “Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN”

PoseModel: An Open-Source Toolkit for Accurate and Robust Automated Behavioral Latent Embedding

A repo for baseline of graph pooling.

An implementation of the Graph Convolution Networks for the Cora, Citeseer, PubMed dataset.

API wrapper for DolarPy

Deep Learning Ecotone Enthusiast

Erreur_404 🚨 est une animation plein écran réalisée avec Pygame 🐍, affichant un “ERREUR 404” ⚠️ saisissant accompagné d’effets glitch 💥 et d’une pluie de caractères à la Matrix 🌌💻. Idéale pour un style hacker 🕶️, une installation artistique 🎨 ou un décor numérique immersif ✨🖥️.

Opto-fmri decoding of locus coeruleus firing patterns using Graph Neural Networks and the BrainGNN framework

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

MetroTwin - Digital Twin for Urban Infrastructure <br/><br/> A graph-based digital twin platform that models city infrastructure and runs simulations to forecast the impact of planning decisions on energy, transport, and environment.

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