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Found 4 papers, 1 papers with code
Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms
We present a method for metric optimization in the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework, by treating the induced Riemannian metric on the space of diffeomorphisms as a kernel in a machine learning context.
Simultaneous Matrix Diagonalization for Structural Brain Networks Classification
This paper considers the problem of brain disease classification based on connectome data.
A Restaurant Process Mixture Model for Connectivity Based Parcellation of the Cortex
One of the primary objectives of human brain mapping is the division of the cortical surface into functionally distinct regions, i. e. parcellation.
An Empirical Study of Continuous Connectivity Degree Sequence Equivalents
In the present work we demonstrate the use of a parcellation free connectivity model based on Poisson point processes.
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