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State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge., , , , , , , , , and 13 other author(s). CoRR, (2020)Benchmarking Deep Nets MRI Reconstruction Models on the Fastmri Publicly Available Dataset., , and . ISBI, page 1441-1445. IEEE, (2020)Spatially regularized wavelet leader scale-free analysis of fMRI data., , and . ISBI, page 1248-1251. IEEE, (2018)Self-Calibrating Nonlinear Reconstruction Algorithms for Variable Density Sampling and Parallel Reception MRI., , , , and . SAM, page 415-419. IEEE, (2018)Modulation of scale-free properties of brain activity in MEG., , , and . ISBI, page 1531-1534. IEEE, (2012)Multivariate semi-blind deconvolution of fMRI time series., , , , and . NeuroImage, (2021)Multi-subject Bayesian Joint Detection and Estimation in fMRI., , , and . PRNI, page 1-4. IEEE, (2014)Impact of perceptual learning on resting-state fMRI connectivity: A supervised classification study., , and . EUSIPCO, page 250-254. IEEE, (2016)Is good old GRAPPA dead?, , , and . CoRR, (2021)Leader-Based Multifractal Analysis for Evi fmri Time Series: Ongoing vs Task-Related Brain Activity., , , , and . ISBI, page 404-407. IEEE, (2007)