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Detecting Brain State Changes by Geometric Deep Learning of Functional Dynamics on Riemannian Manifold., , , , , и . MICCAI (7), том 12907 из Lecture Notes in Computer Science, стр. 543-552. Springer, (2021)Learning Brain Dynamics of Evolving Manifold Functional MRI Data Using Geometric-Attention Neural Network., , , , и . IEEE Trans. Medical Imaging, 41 (10): 2752-2763 (2022)Detecting Changes of Functional Connectivity by Dynamic Graph Embedding Learning., , , и . MICCAI (7), том 12267 из Lecture Notes in Computer Science, стр. 489-497. Springer, (2020)HoloBrain: A Harmonic Holography for Self-organized Brain Function., , , , , , , и . IPMI, том 13939 из Lecture Notes in Computer Science, стр. 29-40. Springer, (2023)Assessing the consistency of community structure in complex networks, , , и . CoRR, (2011)Constructing Multi-scale Connectome Atlas by Learning Graph Laplacian of Common Network., , , , , , и . MICCAI (3), том 11766 из Lecture Notes in Computer Science, стр. 727-735. Springer, (2019)Embedding Functional Brain Networks in Low Dimensional Spaces Using Manifold Learning Techniques., , , , , и . Frontiers Neuroinformatics, (2021)Tensor-based vs. matrix-based rank reduction in dynamic brain connectivity., , , , и . Medical Imaging: Image Processing, том 10574 из SPIE Proceedings, стр. 105740Z. SPIE, (2018)Sliding window correlation analysis: Modulating window shape for dynamic brain connectivity in resting state., , , , и . NeuroImage, (2019)Brain Network Analysis: A Review on Multivariate Analytical Methods., , , и . Brain Connect., 13 (2): 64-79 (марта 2023)