Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods

30 May 2023

Papers citing "Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods"

10 / 10 papers shown

Title
MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI Tobit Klug Kun Wang Stefan Ruschke Reinhard Heckel MedIm 34 1 0 14 Sep 2024
Language models scale reliably with over-training and on downstream tasks S. Gadre Georgios Smyrnis Vaishaal Shankar Suchin Gururangan Mitchell Wortsman ... Y. Carmon Achal Dave Reinhard Heckel Niklas Muennighoff Ludwig Schmidt ALM ELM LRM 103 40 0 13 Mar 2024
A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography Simon Wiedemann Reinhard Heckel 15 7 0 09 Nov 2023
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets Frédéric Wang Han Qi A. D. Goyeneche Reinhard Heckel Michael Lustig Efrat Shimron 19 4 0 05 Aug 2023
Scaling Laws For Deep Learning Based Image Reconstruction Tobit Klug Reinhard Heckel 57 12 0 27 Sep 2022
Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework Chenwenbao Hu Cheng Li Haifeng Wang Qiegen Liu Hairong Zheng Shanshan Wang OOD 75 43 0 26 Sep 2021
Zero-Shot Self-Supervised Learning for MRI Reconstruction Burhaneddin Yaman S. A. Hosseini Mehmet Akçakaya 16 65 0 15 Feb 2021
Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images Tao Huang Songjiang Li Xu Jia Huchuan Lu Jian-zhuo Liu 64 284 0 08 Jan 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,424 0 23 Jan 2020
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 279 39,083 0 01 Sep 2014