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Reinhard Heckel

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Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data

Dec 16, 2023
Kang Lin, Reinhard Heckel

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A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography

Nov 09, 2023
Simon Wiedemann, Reinhard Heckel

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K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets

Aug 05, 2023
Frederic Wang, Han Qi, Alfredo De Goyeneche, Reinhard Heckel, Michael Lustig, Efrat Shimron

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Approximating Positive Homogeneous Functions with Scale Invariant Neural Networks

Aug 05, 2023
Stefan Bamberger, Reinhard Heckel, Felix Krahmer

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Learning Provably Robust Estimators for Inverse Problems via Jittering

Jul 24, 2023
Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel

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Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods

May 30, 2023
Tobit Klug, Dogukan Atik, Reinhard Heckel

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Implicit Neural Networks with Fourier-Feature Inputs for Free-breathing Cardiac MRI Reconstruction

May 11, 2023
Johannes F. Kunz, Stefan Ruschke, Reinhard Heckel

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Zero-Shot Noise2Noise: Efficient Image Denoising without any Data

Mar 20, 2023
Youssef Mansour, Reinhard Heckel

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Test-time Recalibration of Conformal Predictors Under Distribution Shift Based on Unlabeled Examples

Oct 09, 2022
Fatih Furkan Yilmaz, Reinhard Heckel

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Scaling Laws For Deep Learning Based Image Reconstruction

Sep 27, 2022
Tobit Klug, Reinhard Heckel

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