Papers on Graph Pooling for GNN and their bioinformatics application

This project uses graph theory to represent and navigate maps, providing a graphical user interface for visualization and employing Dijkstra's algorithm for finding the shortest paths between intersections. It supports map visualization, pathfinding, and interactive navigation through a command-line application and Swing-based interface.

repo for learning graph neural network

A scikit-learn compatible library for graph kernels

Self-Attention Graph Pooling [ICML-2019]

Streamlit App for Node and Graph Classification and Explainability

Re-implementation of G-Mixup: Graph Data Augmentation for Graph Classification

Few-Shot Graph Classification via distance metric learning.

A curated list of data mining papers about fraud detection.

CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

Pattern Mining for the Classification of Public Procurement Fraud

Knowledge-Aware ICD Coding.

PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)

Signed Whole Graph Embeddings

A PyTorch implementation of DGCNN based on AAAI 2018 paper "An End-to-End Deep Learning Architecture for Graph Classification"

Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'

A package for computing Graph Kernels

Python package for Collective Classification

[IJCNN 2021] Structure-Aware Hierarchical Graph Pooling using Information Bottleneck