Feb 12, 2022 · In this paper, we propose an attention-based hierarchical denoised deep clustering (AHDDC) algorithm to solve the problem, which enables GCN to learn multiple ...
Attention-based hierarchical denoised deep clustering network. https://doi.org/10.1007/s11280-022-01007-4. Journal: World Wide Web, 2022, № 1, p. 441-459.
The influences of the attention mechanism arrangements on five datasets · The role of metric learning · Attention-based hierarchical denoised deep clustering ...
Jun 21, 2024 · This attention-based network architecture includes a feature extraction network, an eigenvector mapping network, and an orthogonalization module ...
Jul 26, 2024 · Through iterative fusion based on denoising and topological embedding, scLEGA generates more compact and robust cell representations that are ...
Aug 9, 2024 · Our approach employs a multi-layer graph convolutional network (GCN) to capture high-order structural relationships between cells, termed as the ...
To this end, we propose a novel deep clustering method named Attention-driven Graph Clustering Network (AGCN). Specifically, AGCN exploits a heterogeneity-wise ...
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In this paper, we propose an adaptive graph convolutional clustering network that alternatively adjusts the graph structure and node representation layer-by- ...
Attention-based hierarchical denoised deep clustering network - 科研通
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Oct 9, 2022 · In this survey, we summarize deep multi-view clustering into three categories: deep embedded clustering based, subspace clustering based, and.