Tootfinder

Network architecture search of X-ray based scientific applications
Adarsha Balaji, Ramyad Hadidi, Gregory Kollmer, Mohammed E. Fouda, Prasanna Balaprakash
https://arxiv.org/abs/2404.10689

Network architecture search of X-ray based scientific applications
X-ray and electron diffraction-based microscopy use bragg peak detection and ptychography to perform 3-D imaging at an atomic resolution. Typically, these techniques are implemented using computationally complex tasks such as a Psuedo-Voigt function or solving a complex inverse problem. Recently, the use of deep neural networks has improved the existing state-of-the-art approaches. However, the design and development of the neural network models depends on time and labor intensive tuning of the…

This https://arxiv.org/abs/2211.06757 has been replaced.
link: https://scholar.google.com/scholar?q=a

DriftRec: Adapting diffusion models to blind JPEG restoration
In this work, we utilize the high-fidelity generation abilities of diffusion models to solve blind JPEG restoration at high compression levels. We propose an elegant modification of the forward stochastic differential equation of diffusion models to adapt them to this restoration task and name our method DriftRec. Comparing DriftRec against an $L_2$ regression baseline with the same network architecture and state-of-the-art techniques for JPEG restoration, we show that our approach can escape t…