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Found 5 papers, 0 papers with code
Discovering the neural correlate informed nosological relation among multiple neuropsychiatric disorders through dual utilisation of diagnostic information
The unravelled nosological relation among diverse types of neuropsychiatric disorders serves as an important precursor in advocating the dimensional approach to psychiatric classification.
Improving the spectral resolution of fMRI signals through the temporal de-correlation approach
The inherent infra-slow, narrowband signal thwarts the fMRI modality in considering as an optimal neuroimaging modality to its alternatives, e. g., EEG and MEG, in investigating the spectral character of cortical activities.
Multiple-view clustering for identifying subject clusters and brain sub-networks using functional connectivity matrices without vectorization
However, when one applies an existing multiple-view clustering method to fMRI data, there is a need to simplify the data structure, independently dealing with elements in a FC matrix, i. e., vectorizing a correlation matrix.
Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions
We propose a novel method for multiple clustering that assumes a co-clustering structure (partitions in both rows and columns of the data matrix) in each view.
A Generalized Natural Actor-Critic Algorithm
In this paper, we describe a generalized Natural Gradient (gNG) by linearly interpolating the two FIMs and propose an efficient implementation for the gNG learning based on a theory of the estimating function, generalized Natural Actor-Critic (gNAC).
