Image response regression via deep neural networks

• Published in: Journal of the Royal Statistical Society. Series B, Statistical methodology Vol. 85; no. 5; pp. 1589 - 1614
• Main Authors: Zhang, Daiwei, Li, Lexin, Sripada, Chandra, Kang, Jian
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.11.2023
• Subjects: Artificial neural networks; Asymptotic methods; Functional magnetic resonance imaging; Heterogeneity; Magnetic resonance imaging; Neural networks; Original; Smoothness; non-parametric regression; varying coefficient models; high-dimensional inference; deep neural networks; functional magnetic resonance imaging; tensor regression

Delineating associations between images and covariates is a central aim of imaging studies. To tackle this problem, we propose a novel non-parametric approach in the framework of spatially varying coefficient models, where the spatially varying functions are estimated through deep neural networks. O...