Popular GitHub Repositories for Gnn

Recommendation Algorithm大规模推荐算法库，包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM，DSIN，SIGN，IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESMM、ESCMM, MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、DMR、GateNet、NAML、DIFM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、Fibinet、ListWise、DeepRec、ENSFM，TiSAS，AutoFIS等，包含经典推荐系统数据集criteo 、movielens等

AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN），图神经网络（GNN），NLP，大数据相关的发展路书(roadmap), 并附海量源码（python，pytorch）带大家消化基本知识点，突破面试，完成从新手到合格工程师的跨越，其中深度学习相关论文附有tensorflow caffe官方源码，应用部分含推荐算法和知识图谱

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

An Industrial Graph Neural Network Framework

A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

Programmable CUDA/C++ GPU Graph Analytics

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

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Code and resources on scalable and efficient Graph Neural Networks (TNNLS 2023)

Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks (ICML 2023)

A PyTorch Graph Neural Network Library

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

tsl: a PyTorch library for processing spatiotemporal data.

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

[NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.

SPIGA: Shape Preserving Facial Landmarks with Graph Attention Networks.

PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)