Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
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Updated
Mar 9, 2023 - Python
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
A library for graph deep learning research
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)
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
Representation-Learning-on-Heterogeneous-Graph
CRSLab is an open-source toolkit for building Conversational Recommender System (CRS).
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
Recipe for a General, Powerful, Scalable Graph Transformer
Deep and conventional community detection related papers, implementations, datasets, and tools. Welcome to contribute to this repository by following the {instruction_for_contribution.pdf} file.
Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch
Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding
Implementation of ICCV19 Paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network"
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).
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