Gnn Python Packages

torch-geometric-temporal

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

tensorflow-gnn

TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

city2graph

Transform geospatial relations into graphs for Graph Neural Networks and network analysis

tf-geometric

Efficient and Friendly Graph Neural Network Library for TensorFlow 1.x and 2.x

causing

Causing: CAUsal INterpretation using Graphs

torch-geometric-signed-directed

PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. The paper is accepted by LoG 2023.

torch-spatiotemporal

tsl: a PyTorch library for processing spatiotemporal data.

fennlp

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.

modssc

ModSSC: A Modular Framework for Semi Supervised Classification

pandadock

PandaDock: Physics based Molecular Docking with GNN Scoring

hugegraph-python

A Python SDK for Apache HugeGraph

mlx-cluster

High-performance graph algorithms optimized for Apple's MLX framework. Features random walks, biased random walks (Node2Vec), and neighbor sampling

ptgnn

A PyTorch Graph Neural Network Library

graph-transformer

An unofficial implementation of Graph Transformer (Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification) - IJCAI 2021

unravelsports

The unravelsports package aims to aid researchers, analysts and enthusiasts by providing intermediary steps in the complex process of turning raw sports data into meaningful information and actionable insights.

lamda-ssl

LAMDA-SSL is an useful toolkit for semi-supervised learning.

spiga

SPIGA: Shape Preserving Facial Landmarks with Graph Attention Networks.

solitairenet

Solitaire deep learning library

graph-learn

Python Interface for Graph Neural Network

quiver-feature

High performance RDMA-based distributed feature collection component for training GNN model on EXTREMELY large graph

hugegraph-llm

The integration of HugeGraph with AI/LLM & GraphRAG

dgcnn

TensorFlow 2 implementation of Deep Graph Convolutional Neural Networks.

neurofhir

Geometric Deep Learning for Clinical Informatics: Converting FHIR to Temporal-Hierarchical Graph Tensors

ncem

ncem. Learning cell communication from spatial graphs of cells.