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Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis
Resting-state functional connectivity states are often identified as clusters of dynamic connectivity patterns. However, existing clustering approaches do not distinguish major states from rarely occurring minor states and hence are sensitive to noise. To address this issue, we propose to model majo...
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| Publicado no: | Inf Process Med Imaging |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7375028/ https://ncbi.nlm.nih.gov/pubmed/32699491 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-20351-1_68 |
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