OpenFGL: A Comprehensive Benchmarks for Federated Graph Learning
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Updated
Jun 2, 2024 - Python
OpenFGL: A Comprehensive Benchmarks for Federated Graph Learning
A Python Library for Graph Outlier Detection (Anomaly Detection)
D<ee>p learning [dev library]
[KDD 2024] Papers about deep learning in epidemic modeling.
[IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.
autoupdate paper list
[NeurIPS 2023] Official implementation of "A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks"
[ICML 2023] Official implementation of "A randomized schur complement based graph augmentor"
🔥 CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification
Advanced Graph Clustering method documentation and implementation (From Spectral Clustering to Deep Graph Clustering)
PyGDA is a Python library for Graph Domain Adaptation.
Official implementation for paper "Can Graph Learning Improve Task Planning?" https://arxiv.org/abs/2405.19119
A list of awesome GNN systems.
Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov
Graph Neural Network Library for PyTorch
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Contextualizing protein representations using deep learning on protein networks and single-cell data
Official implementation of DrugGEN
🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统
This collection of papers can be used to summarize research about graph reinforcement learning for the convenience of researchers.
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