Jonathan Vöglein

According to our database, Jonathan Vöglein authored at least 3 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

A non-parametric statistical inference framework for Deep Learning in current neuroimaging.

Carmen Jimenez-Mesa, Javier Ramírez, John Suckling, Jonathan Vöglein, Johannes Levin, Juan Manuel Górriz

Inf. Fusion, 2023

2022

Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease.

Jeremy F. Strain, Matthew R. Brier, Aaron Tanenbaum, Brian A. Gordon, John E. McCarthy, Aylin Dincer, Daniel S. Marcus, Jasmeer P. Chhatwal, Neill R. Graff-Radford, Gregory S. Day, Christian la Fougère, Richard J. Perrin, Stephen P. Salloway, Peter R. Schofield, Igor Yakushev, Takeshi Ikeuchi, Jonathan Vöglein, John C. Morris, Tammie L. S. Benzinger, Randall J. Bateman, Beau M. Ances, Abraham Z. Snyder

NeuroImage, 2022

2021

Deep Learning in current Neuroimaging: a multivariate approach with power and type I error control but arguable generalization ability.

Carmen Jimenez-Mesa, Javier Ramírez, John Suckling, Jonathan Vöglein, Johannes Levin, Juan Manuel Górriz, Alzheimer's Disease Neuroimaging Initiative, Dominantly Inherited Alzheimer Network (DIAN)

CoRR, 2021