In addition, both aforementioned methods can neither catch the multi-scale information nor use the current clustering labels effectively, which lead to the suboptimal performance. To this end, we proposed a nove
Deep multi-view graph clustering network with weighting mechanism and collaborative training阅读笔记 gauge 2 人赞同了该文章 1.论文背景 随着图卷积网络(GCN)在图嵌入学习中具有强大的功能,同时能够捕获节点特征信息的发展,基于图自编码器的深度多视点图聚类方法已成为一种新的流。虽然他们达到满意的性能,他们仍...
LPA是一种基于图的聚类方法,其中节点的标签基于其邻居的标签进行传播和更新。 基于多图的集成聚类(Ensemble Clustering on Multiple Graphs): 这种方法通过组合多个聚类结果来创建一个更稳定的聚类输出,通常涉及投票或融合策略。 基于核的多图聚类(Kernel-based Multi-Graph Clustering): 使用核技巧来捕捉非线性结构,并结...
As a result, UnitedNet consistently exhibits similar or better unsupervised joint group identification accuracy compared with the single-modality Leiden clustering and other state-of-the-art methods (Fig. 2b and “Methods”). We then performed an ablation analysis by removing the cross-modal ...
Complex networks Brain networks Multi-scale Network neuroscience Multi-resolution Multi-layer Graph theory 1. Introduction Over the past decade, the neuroimaging community has witnessed a paradigm shift. The view that localized populations of neurons and individual brain regions support cognition and behavi...
confirming previous studies that have suggested the existence of multiscale communities in brain anatomical and functional systems39. In the case of the human brain network in Fig.7, we find that communities fall onto spatially contiguous parts of the cerebral cortex, in line with the prevailing ...
Multi-View Attribute Graph Convolution Networks for Clustering(MAGCN)论文学习笔记 gauge 1 人赞同了该文章 1.论文背景 图神经网络(GNNs)在处理图结构数据方面取得了相当大的成就。然而:(1)现有的方法不能将可学习的权值分配给邻域内的不同节点,(2)并且由于同时忽略了节点属性和图重构,缺乏鲁棒性。(3)对于...
Graph-based approach: 3 Proposed Computational Framework 3.1 Clustering algorithm for graph formation 3.2 Cluster-feature Embedding 3.3 Feature-fusion Backbone 3.4 Bidirectioal-graph Convolution Network ...
论文地址:Multi-View Attribute Graph Convolution Networks for Clustering | IJCAI 论文代码:MAGCN 1.多视图属性聚类:MAGCN 1.存在问题:GNN 融入Multi-View Graph 1)他们不能将指定学习的不同权重的分配给邻域内的不同节点; 2)他们可能忽略了进行节点属性和图结构的重构以提高鲁棒性; ...
论文标题:Multi-view Contrastive Graph Clustering论文作者:Erlin Pan、Zhao Kang论文来源:2021, NeurIPS论文地址:download论文代码:download1 介绍本文贡献:使用Graph Filter 过滤了高阶噪声数据; 提出Graph Contrastive Regularizer 改善了视图的质量; 2 方法