• Aucun résultat trouvé

Sparse tensor dimensionality reduction with application to clustering of functional connectivity

N/A
N/A
Protected

Academic year: 2021

Partager "Sparse tensor dimensionality reduction with application to clustering of functional connectivity"

Copied!
13
0
0

Texte intégral

Références

Documents relatifs

Influence of Vascular Variant of the Posterior Cerebral Artery (PCA) on Cerebral Blood Flow, Vascular Response to CO2 and Static Functional Connectivity... Influence of Vascular

The statistician community developed numerous models for handling such datasets and we fo- cus here on four regression models: two standards as the functional linear model and

Similar results were obtained for the number of transitions between states of functional network topology. The total number of transitions was significantly lower in the IPKA

According to this observation, the over-represented proteins in trajectories from core 1 and 2 clearly discriminate the canonical pathways associated with TGF-β receptor-dependent

In applications where adjacency-constrained cluster- ing is relevant, such as Hi-C and GWAS data analysis, this quadratic time complexity is a major practical bot- tleneck because p

The paper is organized as follows: in Section 2, we provide an overview of related works in the field of dimensionality reduction focusing on HSIs, and point out the need

of brain activity in different states, and subjective estimates of performance (24) to investigate which aspects of functional con- nectivity correlate with the wide

Gray matter volume changes were analyzed using whole-brain voxel-based morphometry, and resting-state functional connectivity was investigated using a seed-based analysis, with