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Restricted Boltzmann Machines for Neuroimaging: an Application in Identifying Intrinsic Networks
Matrix factorization models are the current dominant approach for resolving meaningful data-driven features in neuroimaging data. Among them, independent component analysis (ICA) is arguably the most widely used for identifying functional networks, and its success has led to a number of versatile ex...
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| Publicado no: | Neuroimage |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4348021/ https://ncbi.nlm.nih.gov/pubmed/24680869 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2014.03.048 |
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