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Joint Estimation of Neural Events and Hemodynamic Response Functions from Task fMRI via Convolutional Neural Networks.

, , , , , and . MLCN@MICCAI, volume 14312 of Lecture Notes in Computer Science, page 67-78. Springer, (2023)

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93% Efficiency and 0.99 power factor in pseudo-linear LED driver., , , , , , , , , and . A-SSCC, page 53-56. IEEE, (2016)Joint Estimation of Neural Events and Hemodynamic Response Functions from Task fMRI via Convolutional Neural Networks., , , , , and . MLCN@MICCAI, volume 14312 of Lecture Notes in Computer Science, page 67-78. Springer, (2023)An Efficient Cluster Construction Strategy for Wireless Sensor Networks., , and . IBICA, page 328-331. IEEE Computer Society, (2011)Nonlinear Conditional Time-Varying Granger Causality of Task fMRI via Deep Stacking Networks and Adaptive Convolutional Kernels., , , and . MICCAI (1), volume 13431 of Lecture Notes in Computer Science, page 271-281. Springer, (2022)Deep Stacking Networks for Conditional Nonlinear Granger Causal Modeling of fMRI Data., , , and . MLCN@MICCAI, volume 13001 of Lecture Notes in Computer Science, page 113-124. Springer, (2021)TARDIS: An updated artificial intelligence model to predict linear accelerator machine parameters at treatment delivery., , , and . SoftwareX, (2022)An adaptive capacity enhancement strategy for sector-based cellular systems., , , , and . Comput. Math. Appl., 64 (5): 1462-1472 (2012)