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Brain Functional Connectivity Analysis via Graphical Deep Learning.

, , , , , , , and . IEEE Trans. Biomed. Eng., 69 (5): 1696-1706 (2022)

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zMesh: Exploring Application Characteristics to Improve Lossy Compression Ratio for Adaptive Mesh Refinement., , , , , and . IPDPS, page 402-411. IEEE, (2021)Graph Laplacian learning based Fourier Transform for brain network analysis with resting state fMRI., , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 11317 of SPIE Proceedings, page 113171G. SPIE, (2020)CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents., , , , , , , , , and 3 other author(s). ICLR, OpenReview.net, (2024)Integration of network topological features and graph Fourier transform for fMRI data analysis., , , , and . ISBI, page 92-96. IEEE, (2018)A Data-driven Approach to Harvesting Latent Reduced Models to Precondition Lossy Compression for Scientific Data., , , , , , and . IEEE Trans. Big Data, 9 (3): 949-963 (June 2023)ZFP-X: Efficient Embedded Coding for Accelerating Lossy Floating Point Compression., , , , and . IPDPS, page 1041-1050. IEEE, (2023)A design approach for event-driven optimization in complex air conditioning systems., , , and . CASE, page 912-917. IEEE, (2017)Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome., , , , , , , and . NeuroImage, (2024)CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents., , , , , , , , , and 4 other author(s). CoRR, (2024)Brain Functional Connectivity Analysis via Graphical Deep Learning., , , , , , , and . IEEE Trans. Biomed. Eng., 69 (5): 1696-1706 (2022)