A library for graph deep learning research
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
Heterogeneous Graph Neural Network
A list of recent papers about Graph Neural Network methods applied in NLP areas.
Neural Graph Collaborative Filtering, SIGIR2019
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
Recipe for a General, Powerful, Scalable Graph Transformer
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).
A repository of pretty cool datasets that I collected for network science and machine learning research.
[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen
Deep and conventional community detection related papers, implementations, datasets, and tools.
CRSLab is an open-source toolkit for building Conversational Recommender System (CRS).
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch
Representation-Learning-on-Heterogeneous-Graph
Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
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