Graph Neural Network Library for PyTorch
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Updated
May 10, 2024 - Python
Graph Neural Network Library for PyTorch
Python package built to ease deep learning on graph, on top of existing DL frameworks.
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Anomaly detection related books, papers, videos, and toolboxes
links to conference publications in graph-based deep learning
SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)
A unified, comprehensive and efficient recommendation library
A distributed graph deep learning framework.
Repository for benchmarking graph neural networks
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StellarGraph - Machine Learning on Graphs
🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统
Benchmark datasets, data loaders, and evaluators for graph machine learning
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Graph Neural Networks with Keras and Tensorflow 2.
CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
[AAAI 2019] Source code and datasets for "Session-based Recommendation with Graph Neural Networks"
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply
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