zhenying123

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【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容

CTGCN

CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056

evolvegcn

EvolveGCN-1

Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

FairDLA

FairDLA_new

Source codes of FairDLA

GraphMAE

GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22

MaskGAE

[KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders

NLP_ability

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

pytorch_geometric

Graph Neural Network Library for PyTorch

zhenying123/FairDLA

zhenying123/FairDLA_new

Source codes of FairDLA

zhenying123/-

【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容

zhenying123/CTGCN

CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056

zhenying123/evolvegcn

zhenying123/EvolveGCN-1

Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

zhenying123/GraphMAE

GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22

zhenying123/MaskGAE

[KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders

zhenying123/NLP_ability

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

zhenying123/pytorch_geometric

Graph Neural Network Library for PyTorch