Deep learning methods often struggle with noisy data caused by sudden changes and fail to capture essential temporal information for community evolution. Additionally, data security concerns are frequently over
Clustering spatial transcriptomics data. Bioinformatics 38, 997–1004 (2022). Article Google Scholar Hu, J. et al. SpaGCN: integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network. Nat. Methods 18, 1342–...
Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder Breakthrough technologies for spatially resolved transcriptomics have enabled genome-wide profiling of gene expressions in captured locations. Here the authors integrate gene expressions and spatial ...
Graph data models are useful to store, process and analyse highly interlinked data [1]. This is achieved through the use of graph theory to store data in the form of nodes and edges [2]. With the recent rise in the popularity of graph databases, which rely on graph data models to stor...
A second group lists methods depending on the cluster model acquired such as hierarchical [4], centroid (as in K-means [5]), distribution such as expectation maximization [6], density [7,8], subspace, group, and graph-based models [9,10]. Thirdly, depending on the relationship type ...
The proposed scheme aims to balance the tradeoff between the number of common channels and the number of nodes (cluster size) in a cluster. First, a set of CR users and a set of channels are two disjoint sets of a bipartite graph in which the channels available to CR users are ...
论文阅读06——《CaEGCN: Cross-Attention Fusion based Enhanced Graph Convolutional Network for Clustering》 Ideas: Model: 交叉注意力融合模块 图自编码器 Ideas: 提出一种基于端到端的交叉注意力融合的深度聚类框架,其中交叉注意力融合模块创造性地将图卷积自编码器模块和自编码器模块多层级连起来 ...
Linkage Based Face Clustering via Graph Convolution Network Abstract 在本文中,我们为人脸聚类任务提出了一种精确和可扩展的方法。我们的目标是将一组人脸按照他们潜在的身份进行分组。我们将此任务表述为一个连接预测问题:如果两个人脸具有相同的身份,那么它们之间存在连接。关键的思想是,我们在特征空间中找到一个实例...
Abstractly, a tumor progression pathway is a directed graph with nodes corresponding to archetypal tumor stages and a directed edge denoting possible progression from one stage to another (see Figure1). Tumor progression pathways are constructed based on the following characteristics: (1) most CpG ...
proposed a fast relaxed clustering algorithm based on graph theory. The asymptotic time complexity of this algorithm is linearly related to the data capacity when applied to larger-scale datasets [10]. Charles et al. proposed an efficient K-means clustering algorithm, which uses precomputed ...