Probabilistic Structure Learning for EEG/MEG Source Imaging With Hierarchical Graph Priors is a research paper published in IEEE Transactions on Medical Imaging (2020). On theSindex it has a DataRank of 0. It has been cited 32 times.
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NSF
Grant: DMS-2009689
NSF
Grant: DMS-1522786
NSF
Grant: CAREER 1846690
NSF
Grant: CCF-1527104
NSF
Grant: DMS-1719620
NIH
Grant: R01AG054081
NIH
Grant: R01AG056015
National Institutes of Health
Grant: 5R01AG056015-04
The Aging Brain Under General Anesthesia: Neurophysiology, Neuroimaging Biomarkers of Aging and Alzheimer's Disease, and Post-Operative Cognitive Outcomes
National Science Foundation
Grant: 1527104
AF: Small: Collaborative Research: Mathematical Theory and Fast Algorithms for Rayleigh Quotient-type Optimizations
National Science Foundation
Grant: 1522786
A Non-Convex Approach for Signal and Image Processing
National Science Foundation
Grant: 1719620
Ubiquitous Doubling Algorithms for Nonlinear Matrix Equations and Applications
National Science Foundation
Grant: 1846690
CAREER: Mathematical Modeling from Data to Insights and Beyond
National Institutes of Health
Grant: 1R01AG054081-01A1
Noninvasive Low-cost Biomarkers for Preclinical Diagnosis and Longitudinal Tracking of Alzheimer's Disease Using Sleep and Resting State EEG
Tiny Blue Dot Foundation
FWCI
2.89
Citation Percentile
0.9%
Citation Trend
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