然而,我们观察到,现有文献有很多需要提升的地方,如:1)缺乏一种动态融合机制来有选择地整合和改善图的结构和节点属性信息以进行共识表示学习; 2)未能利用双方提取的信息进行鲁棒目标分布生成(可以理解为DEC中的soft labels分配)。为了解决上述问题,论文提出了deep fusion clustering network (DFCN)。具体地说,该网络中...
论文标题:Deep Fusion Clustering Network 论文作者:Wenxuan Tu, Sihang Zhou, Xinwang Liu, Xifeng Guo, Zhiping Cai, En Zhu, Jieren Cheng 论文来源:2020, AAAI 论文地址:download 论文代码:download 1 Introduction 先前工作存在的问题: 缺少一种动态融合机制将属性信息和结构信息融合起来; ...
论文阅读“Deep Fusion Clustering Network” Tu W, Zhou S, Liu X, et al. Deep fusion clustering network[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2021, 35(11): 9978-9987. 摘要导读 近年来,利用图神经网络GNN捕获结构信息并结合自编码器AE进行深度聚类的方式已经展现出强劲的...
Variational Structural Deep Clustering Network Wu, Haomin,Tang, Bin,Chen, Feiyu,... - International Conference on Intelligent Computing - 2024 - 被引量: 0 scDFN: enhancing single-cell RNA-seq clustering with deep fusion networks Liu Tianxiang,Jia C...
Deep Fusion Clustering NetworkWenxuan TuSihang ZhouXinwang LiuXifeng GuoZhiping CaiEn ZhuJieren ChengNational Conference on Artificial Intelligence
Here we provide an implementation of Deep Fusion Clustering Network (DFCN) in PyTorch, along with an execution example on the DBLP dataset (due to file size limit). The repository is organised as follows: load_data.py: processes the dataset before passing to the network. ...
AAAI 2021-Deep Fusion Clustering Network self-supervised-learninggraph-neural-networkdeep-clustering UpdatedMar 4, 2024 Python Jupyter notebooks for predicting tides, using unsupervised neural net clustering. tidescnn-kerasoceansdeep-clustering UpdatedFeb 12, 2024 ...
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...
AGCN主要包含KNN模块、DNN模块、AGCN-H模块、AGCN-S模块、双重自监督模块。其中KNN模块、DNN模块以及双重自监督模块与SDCN一致,不再详细讲解,SDCN详细请看论文阅读03——《Structural Deep Clustering Network》。 Marigold 2022/06/17 4990 论文阅读06——《CaEGCN: Cross-Attention Fusion based Enhanced Graph ...
To capture the information of human heads of multiple scales, we proposed a fusion strategy that combines the information from different layers of the network. The framework estimates the crowd density and crowd count simultaneously. The framework predicts density and count both in low- and high-de...