The troublesome kernel--On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems
NM Gottschling, V Antun, AC Hansen… - arXiv preprint arXiv …, 2020 - arxiv.org
Methods inspired by Artificial Intelligence (AI) are starting to fundamentally change
computational science and engineering through breakthrough performances on challenging …
computational science and engineering through breakthrough performances on challenging …
NESTANets: Stable, accurate and efficient neural networks for analysis-sparse inverse problems
M Neyra-Nesterenko, B Adcock - Sampling Theory, Signal Processing, and …, 2023 - Springer
Solving inverse problems is a fundamental component of science, engineering and
mathematics. With the advent of deep learning, deep neural networks have significant …
mathematics. With the advent of deep learning, deep neural networks have significant …
Learning to sample in Cartesian MRI
T Sanchez - arXiv preprint arXiv:2312.04327, 2023 - arxiv.org
Despite its exceptional soft tissue contrast, Magnetic Resonance Imaging (MRI) faces the
challenge of long scanning times compared to other modalities like X-ray radiography …
challenge of long scanning times compared to other modalities like X-ray radiography …