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Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge., , , , , , , , , and 1 other author(s). CoRR, (2020)Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction., , , , , , , , , and 13 other author(s). IEEE Trans. Medical Imaging, 40 (9): 2306-2317 (2021)Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge., , , , , , , , , and 31 other author(s). MLMIR@MICCAI, volume 12964 of Lecture Notes in Computer Science, page 25-34. Springer, (2021)Latent Discretization for Continuous-time Sequence Compression., , , , and . CoRR, (2022)Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions., , , , , , and . MLMIR@MICCAI, volume 11905 of Lecture Notes in Computer Science, page 71-79. Springer, (2019)fastMRI: An Open Dataset and Benchmarks for Accelerated MRI., , , , , , , , , and 13 other author(s). CoRR, (2018)Fast MR image reconstruction with orthogonal wavelet regularization via shift-variant shrinkage., and . ICIP, page 3651-3655. IEEE, (2014)COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction., , , , , , , , , and . CoRR, (2021)Training-free Linear Image Inversion via Flows., , , and . CoRR, (2023)State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge., , , , , , , , , and 13 other author(s). CoRR, (2020)