NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:3995
Title:Manifold-regression to predict from MEG/EEG brain signals without source modeling

This paper presents a way to perform regression on a Riemannian manifold using rank-deficient covariance matrices. This is a novel approach to a new problem of age prediction from resting-state MEG. Reviewers agree this is a worthwhile contribution but have many suggestions for improvements that the authors are advised to consider.