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Found 4 papers, 1 papers with code
Tangent functional connectomes uncover more unique phenotypic traits
(ii) In tangent-FCs, Main-diagonal regularization prior to tangent space projection was critical for ID rate when using Euclidean distance, whereas barely affected ID rates when using correlation distance.
Geodesic distance on optimally regularized functional connectomes uncovers individual fingerprints
Thus, an optimal regularization must be estimated on each dataset to uncover the most differentiable across-subject and reproducible within-subject geodesic distances between FCs.
A Sparsity Inducing Nuclear-Norm Estimator (SpINNEr) for Matrix-Variate Regression in Brain Connectivity Analysis
We present an alternative approach - regularized matrix regression - where the matrix of regression coefficients is defined as a solution to the specific optimization problem.
Regression Trees for Longitudinal Data
We have proposed LongCART algorithm to construct regression tree for the longitudinal data.
