Starling: Introducing a mesoscopic scale with Confluence for Graph Clustering. [PDF]
Gaume B.
europepmc +1 more source
Dynamic Graph Clustering Learning for Unsupervised Diabetic Retinopathy Classification. [PDF]
Yu C, Pei H.
europepmc +1 more source
Building clustering method that integrates graph attention networks and spectral clustering
Clustering is an unsupervised learning method; however, it cannot be directly applied to complex building features to reveal the deep-level intrinsic relationships between buildings and assimilate the cartographic experience of experts.
Guoqing Chen, Haizhong Qian
doaj +1 more source
netANOVA: novel graph clustering technique with significance assessment via hierarchical ANOVA. [PDF]
Duroux D, Van Steen K.
europepmc +1 more source
SymptomGraph: Identifying Symptom Clusters from Narrative Clinical Notes using Graph Clustering. [PDF]
Tahabi FM, Storey S, Luo X.
europepmc +1 more source
It is common knowledge that there is no single best strategy for graph clustering, which justifies a plethora of existing approaches. In this paper, we present a general memetic algorithm, VieClus, to tackle the graph clustering problem. This algorithm can be adapted to optimize different objective functions.
Biedermann, Sonja +3 more
openaire +5 more sources
Diverse representation-guided graph learning for multi-view metric clustering
Multi-view graph clustering has garnered tremendous interest for its capability to effectively segregate data by harnessing information from multiple graphs representing distinct views.
Xiaoshuang Sang +3 more
doaj +1 more source
gcMECM: graph clustering of mutual exclusivity of cancer mutations. [PDF]
Hu Y, Yan C, Chen Q, Meerzaman D.
europepmc +1 more source
MLG: multilayer graph clustering for multi-condition scRNA-seq data. [PDF]
Lu S +5 more
europepmc +1 more source
MAGUS: Multiple sequence Alignment using Graph clUStering. [PDF]
Smirnov V, Warnow T.
europepmc +1 more source

