Advanced Graph Clustering method documentation and implementation (From Spectral Clustering to Deep Graph Clustering)

Graph Neural Network Library for PyTorch

Redes convolucionales definidas en grafos para la predicción de nuevas asociaciones gen-enfermedad

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convol…

A set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.

Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).

Multi-hop Graph Transformer Network for 3D Human Pose Estimation

A novel architecture and training strategy for graph neural networks (GNN). The proposed architecture, named as Autoencoder-Aided GNN (AA-GNN), compresses the convolutional features at multiple hidden layers, hinging on a novel end-to-end training procedure that learns different graph representations per each layer. As a result, the computationa…

Low-Level Graph Neural Network Operators for PyG

Multilabel Aspect Prediction using Graph Convolutional Networks

Graph Reasoned Multi-Scale Road Segmentation in Remote Sensing Imagery

Source Codes: Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks--AAAI 2020

MOFGalaxyNet aims to create a social network for Metal-Organic Frameworks (MOFs) and predict their properties using Graph Convolutional Networks (GCN). It fosters collaboration and exploration in the field of MOFs through social network analysis and machine learning.

This is the repository for the collection of Graph-based Deep Learning for Communication Networks.

CellSNAP: Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data

A pytorch adversarial library for attack and defense methods on images and graphs

GraphPro is a versatile and pluggable OO python library designed for leveraging deep graph learning representations to gain insights into structural proteins and their conformations

[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

Code for "DyGCN: Dynamic Graph Embedding with Graph Convolutional Network"