论文笔记:Attributed Graph Clustering: A Deep Attentional Embedding Approach,程序员大本营,技术文章内容聚合第一站。
论文信息 论文标题:Deep Graph Clustering via Mutual Information Maximization and Mixture Model论文作者:Maedeh Ahmadi, Mehran Safayani, Abdolreza Mirzaei论文来源:2022,
1. 引言 这篇博文主要是对论文“Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embedding”的整理总结,这篇文章将图嵌入与概率深度高斯混合模型相结合,使网络学习到符合全局模型和局部结构约束的强大特征表示。将样本作为图上的节点,并最小化它们的后验分布之间的加权距离,在这里使用Jenson-...
machine-learningdata-miningdeep-learninggraph-clusteringgraph-attention-networksself-supervised-learninggraph-convolutional-neural-networksdeep-clusteringdeep-graph-clusteringdeep-graph-clustering-framework UpdatedDec 17, 2024 Python Deep Conditional Census-Constrained Clustering (DeepC4) for Large-scale Multi-task...
论文阅读02——《Attributed Graph Clustering: A Deep Attentional Embedding Approach》 Ideas: Model: Two-step DAEGC 图注意力自动编码器 自训练聚类模块 具体算法流程 Ideas: Two-step的图嵌入方法不是目标导向的,聚类效果不好,提出一种基于目标导向的属性图聚类框架。
这篇文章是在《Attention-driven Graph Clustering Network》的基础上进行优化,模型的基础结构没变,增加了一个分布融合模块,以及新型的双重自监督,为什么说新,接下来会详细解释。 与AGCN相似的内容就不再介绍,下面详细介绍分布融合模块和双重自监督模块。分布融合模块 顾名思义,分布融合就是将不同的分布通过某种方式结...
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Recently deep learning has been successfully adopted in many applications such as speech recognition and image classification. In this work, we explore the possibility of employing deep learning in graph clustering. We propose a simple method, which first learns a nonlinear embedding of the original ...
Among these methods, Deep Embedded Clustering (DEC) [65] stands out as a pioneering approach inspired by t-SNE, tailored for handling clustering assignments and latent feature representations. DEC initiates network training by pre-training an AE, followed by fine-tuning the encoder. This fine-...
Attributed Graph Clustering: A Deep Attentional Embedding Approach论文阅读笔记。, 视频播放量 569、弹幕量 1、点赞数 6、投硬币枚数 3、收藏人数 18、转发人数 2, 视频作者 庆述, 作者简介 ,相关视频:【自制】+网络结构平衡性判别 + (无字幕),【教程】+论文阅读-