TREAT

Graph Neural Network Library for PyTorch

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Anomaly detection related books, papers, videos, and toolboxes

Code for "Training-free Graph Neural Networks and the Power of Labels as Features" (TMLR 2024)

Codes and datasets for NeurIPS21 paper “Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach”

Official PyTorch implementation of PTS/PSRN: Fast and efficient symbolic expression discovery through parallelized tree search. Evaluates millions of expressions simultaneously on GPU with automated subtree reuse.

links to conference publications in graph-based deep learning

A unified, comprehensive and efficient recommendation library

SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)

? ? ? ? GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统