图神经网络文章推荐

    科技2022-07-10  101

    1. GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media

    论文:https://arxiv.org/pdf/2004.11648.pdf

    代码:https://github.com/l852888/GCAN

    论文解析:https://blog.csdn.net/qq_27590277/article/details/108162740

     

    2. Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification

    代码、论文和解析:https://mp.weixin.qq.com/s/eCmvUaM4Vg5KCFQJcRO-TQ

     

    3. 基于图模型的推荐系统(综述)

    论文和解析:https://mp.weixin.qq.com/s/zrjqPLy3FTb-czmozss31A

     

    4. Deep Learning Based Text Classification: A Comprehensive Review(文本分类综述)

    论文链接:https://arxiv.org/abs/2004.03705

    论文解析:https://zhuanlan.zhihu.com/p/129271523

     

    5. 2019年,异质图神经网络领域有哪些值得读的顶会论文?

    论文简介和代码:

    https://zhuanlan.zhihu.com/p/95933043?utm_source=wechat_session&utm_medium=social&s_r=0

     

    6. 图神经网络!2020 AI研究趋势!是什么?有什么用?

    https://mp.weixin.qq.com/s/r4_5GwA8Olqh6M1p_6eYPg

     

    7. 近期必读的五篇顶会 ACL 2020【图神经网络 (GNN) 】相关论文

    https://mp.weixin.qq.com/s/9ciuynE6jDZ2Hbm7_SH89w

     

    8. 图神经网络GNN2019-2020顶会论文列表

    https://mp.weixin.qq.com/s/8GzrzSDj1txdISRgvFM_aQ

     

    9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

    论文解析和代码:https://www.cnblogs.com/zhanghaiyan/p/12152664.html

    论文:https://arxiv.org/pdf/1810.04805.pdf

     

    10. PRADO 模型:性能媲美BERT,但参数量仅为1/300,这是谷歌最新的NLP模型

    论文、解析和代码:https://mp.weixin.qq.com/s/WMI8U6v4pqc1BePKSTTEgQ

     

    11.EMNLP 2019开源论文:针对短文本分类的异质图注意力网络

    解析:https://mp.weixin.qq.com/s/eCmvUaM4Vg5KCFQJcRO-TQ

    论文:https://www.paperweekly.site/papers/3211

    代码:https://github.com/ytc272098215/HGAT

     

    12.宾大最新《图神经网络》课程

    https://mp.weixin.qq.com/s/V1g1rUBBAhI5Wj1z5DFzeQ

     

    13.机器学习算法优缺点对比(汇总篇)

    https://mp.weixin.qq.com/s/sfiP1LgNMv4uDOcuCDZ6lw

     

    14.2020年最新图神经网络相关的论文 & 书籍 & 代码& 视频课程等学习资源集合

    https://mp.weixin.qq.com/s/YKRjoJUc0Y1UQzk8xPAw9w

     

    15.从发展历史视角解析Transformer:从全连接CNN到Transformer

    https://mp.weixin.qq.com/s/h1fdIHQiPt6MfaaQjKe9zQ

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