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Accessing dynamic functional connectivity using l0-regularized sparse-smooth inverse covariance estimation from fMRI.

, , , , , , , , and . Neurocomputing, (2021)

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Independent component analysis by complex nonlinearities., , and . ICASSP (5), page 525-528. IEEE, (2004)IVA for multi-subject FMRI analysis: A comparative study using a new simulation toolbox., , , , and . MLSP, page 1-6. IEEE, (2011)Fused Estimation of Sparse Connectivity Patterns From Rest fMRI - Application to Comparison of Children and Adult Brains., , , , and . IEEE Trans. Med. Imaging, 37 (10): 2165-2175 (2018)Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data., , and . CoRR, (2016)Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint., , , , , and . IEEE Trans. Medical Imaging, 39 (4): 844-853 (2020)A Joint Analysis of Multi-Paradigm fMRI Data With Its Application to Cognitive Study., , , , , , and . IEEE Trans. Medical Imaging, 40 (3): 951-962 (2021)A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States., , , , , and . Brain Connect., 11 (2): 132-145 (2021)A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age., , , , , and . Brain Connect., 14 (2): 130-140 (2024)Constrained Source-Based Morphometry Identifies Structural Networks Associated with Default Mode Network., , , , , and . Brain Connect., 2 (1): 33-43 (2012)Decentralized Brain Age Estimation Using MRI Data., , , , , , , , and . Neuroinformatics, 20 (4): 981-990 (2022)