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awesome-wechat-weapp

微信小程序开发资源汇总 :100:

competitive-recsys

A collection of resources for Recommender Systems (RecSys)

dgi

Deep Graph Infomax (https://arxiv.org/abs/1809.10341)

glados-checkin-1

gnnpapers

Must-read papers on graph neural networks (GNN)

google-research

Google Research

graphembedding

Implementation and experiments of graph embedding algorithms.deep walk,LINE(Large-scale Information Network Embedding),node2vec,SDNE(Structural Deep Network Embedding),struc2vec

grarep

A SciPy implementation of "GraRep: Learning Graph Representations with Global Structural Information" (WWW 2015).

line

TensorFlow implementation of paper "LINE: Large-scale Information Network Embedding" by Jian Tang, et al.

link-prediction-methods

Link prediction resources, including algorithms, papers, datasets, examples and so on.

msnews.github.io

ogb

Benchmark datasets, data loaders, and evaluators for graph machine learning

pytorch_geometric

Geometric Deep Learning Extension Library for PyTorch

ranksys

Java 8 Recommender Systems framework for novelty, diversity and much more

recbole

A unified, comprehensive and efficient recommendation library

recommenders

Best Practices on Recommendation Systems

rsalgorithms

Some algorithms about traditional and social recommendation.

rspapers

A Curated List of Must-read Papers on Recommender System.

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.