Graph Neural Network Library for PyTorch
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Updated
Sep 3, 2024 - Python
Graph Neural Network Library for PyTorch
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Anomaly detection related books, papers, videos, and toolboxes
links to conference publications in graph-based deep learning
A unified, comprehensive and efficient recommendation library
🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统
SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)
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StellarGraph - Machine Learning on Graphs
A distributed graph deep learning framework.
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Repository for benchmarking graph neural networks
Graph Neural Networks with Keras and Tensorflow 2.
Benchmark datasets, data loaders, and evaluators for graph machine learning
😎 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.
CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
A powerful and flexible machine learning platform for drug discovery
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