Graph Network in Tensorflow

The PyTorch version of gfNN implemented by the paper.

New York Stock Exchange Temporal Graph Construction and Node Regression for Price Prediction

Generative Neural Networks for Horse Image Colourization using Autoencoders. Reconstructing MNIST digits using Convolutional Autoencoders and GANs (Generative Adversarial Networks/ Generator-Discriminator). Adversarial Attack examples with MNIST.

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

Graph neural network modeling team performance through causal dynamics of internal dynamics, external collaborations, and contextual factors from Complexity Sciences.

Enhance supply chain forecasting with GRAPHINE, a novel Virtual Node Diffusion-Convolutional RNN for improved fuel efficiency and accurate spatiotemporal modeling. 🚀📊

Modeling Protein Activities and Mutations with Graph Neural Networks: Insights into Hemophilia

Node Classification on large Knowledge Graphs of Cora Dataset using Graph Neural Network (GNN) in Pytorch.

A collection of image captioning algorithms

This repository contains implementation of Graph Attention Networks(GATs) using Pytorch.

Collection of Machine Learning and GNN methods for Molecular Property Prediction Task

Research exam paper repo. Title: Scalability and Efficiency of Graph Neural Networks

Attention Guided Graph Convolutional Networks for Relation Extraction (authors' PyTorch implementation for the ACL19 paper)

The problem of finding the shortest path in a graph is of great significance in numerous domains, including transportation planning, network optimization, and social network analysis.

my own pytorch learning tutorial

A graph neural network for studying bacterial gene regulation

Supporting material for Academy Course DAT31050

Implementation in Pytorch of the article "E(n) Equivariant Graph Neural Network" - Satorras et al.