Extended Invariant Information Clustering Is Effective for Leave-One-Site-Out Cross-Validation in Resting State Functional Connectivity Modeling
Herein, we propose a new deep neural network model based on invariant information clustering (IIC), proposed by Ji et al., to improve the modeling performance of the leave-one-site-out cross-validation (LOSO-CV) for a multi-source dataset. Our Extended IIC (EIIC) is a type of contrastive learning; h...
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Autores principales: | Naoki Okamoto, Hiroyuki Akama |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/e42e2713bca34346812a69bfb7b2d8bf |
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