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competition

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dian_wang

ecct

Error Correction Code Transformer

ens

finder

FINDER - FInding key players in complex Networks through DEep Reinforcement learning (Nature Machine Intelligence)

gcn-lpa

A tensorflow implementation of GCN-LPA

gcn-lpa-pytorch

A PyTorch Implementation of GCN-LPA

grami

GraMi is a novel framework for frequent subgraph mining in a single large graph, GraMi outperforms existing techniques by 2 orders of magnitudes. GraMi supports finding frequent subgraphs as well as frequent patterns, Compared to subgraphs, patterns offer a more powerful version of matching that captures transitive interactions between graph nodes (like friend of a friend) which are very common in modern applications. Also, GraMi supports user-defined structural and semantic constraints over the results, as well as approximate results. For more details, check our paper: Mohammed Elseidy, Ehab Abdelhamid, Spiros Skiadopoulos, and Panos Kalnis. GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph. PVLDB, 7(7):517-528, 2014.

imp

Influence maximize problem with IC model (degree discount IC , new Greedy) and LT model (SIMPATH)

jieba

结巴中文分词

misticl

Code repository for Knowledge and Information Systems paper titled 'Accelerating Pattern-Based Time Series Classification - A Linear Time and Space String Mining Approach' by Atif Raza and Stefan Kramer

planb

sagpool

Official PyTorch Implementation of SAGPool - ICML 2019

temporal-kg

时序知识图谱与GCN的文献总结

tsanalysis

时间序列的分析与预测，以《绍宋》小说数据为例

viz

wordcloud

中文文本的词云生成（以《三体》为例）