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A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces., , , , and . CoRR, (2020)Group linear non-Gaussian component analysis with applications to neuroimaging., , , , and . Comput. Stat. Data Anal., (2022)Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations., , , , , , and . NeuroImage, (2021)Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference., , , , , and . J. Comput. Graph. Stat., 32 (2): 413-433 (April 2023)Parsing Heterogeneity in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder with Individual Connectome Mapping., , , , , and . Brain Connect., 9 (9): 673-691 (2019)Corrigendum to 'Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity': Neuroimage 2022 Oct 15;260:119434., , , , , , and . NeuroImage, (July 2023)Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characterizations., , , , , , and . CoRR, (2020)Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI., , , , , , , , and . NeuroImage, (2014)A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes., , , , , , and . CoRR, (2021)M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations., , , , , and . MIDL, volume 143 of Proceedings of Machine Learning Research, page 119-130. PMLR, (2021)