The ARI and NMI of SpaMWGDA and seven competing methods on Gaussian Noise 10% DLPFC dataset.

<p>The ARI and NMI of SpaMWGDA and seven competing methods on Gaussian Noise 10% DLPFC dataset.</p>

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Bibliografische gegevens
Hoofdauteur:	Lin Yuan (46306) (author)
Andere auteurs:	Boyuan Meng (22607954) (author), Qingxiang Wang (2637916) (author), Chunyu Hu (12464817) (author), Cuihong Wang (429362) (author), De-Shuang Huang (396909) (author)
Gepubliceerd in:	2025
Onderwerpen:	Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified level attention mechanism fixed similarity metric analyse tissue structure spatial domain identification identifying spatial domains achieved impressive results div >< p combining data augmentation view gcn encoder data augmentation spatial transcriptomics spatial information experimental results weighted fusion trajectory inference spot features source code rapid development large number key features introduce noise gene features deep learning contrastive learning cannot efficiently also show
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