4 papers
Imaging with super-resolution in changing random media
Alexander Christie, Matan Leibovich, Miguel Moscoso +3
We develop an imaging algorithm that exploits strong scattering to achieve super-resolution in changing random media. The method processes large and diverse array datasets using sp…
Atomic Depth Estimation From Noisy Electron Microscopy Data Via Deep Learning
Matan Leibovich, Mai Tan, Ramon Manzorro +4
We present a novel approach for extracting 3D atomic-level information from transmission electron microscopy (TEM) images affected by significant noise. The approach is based on fo…
Super-resolution in disordered media using neural networks
Alexander Christie, Matan Leibovich, Miguel Moscoso +3
We propose a methodology that exploits large and diverse data sets to accurately estimate the ambient medium's Green's functions in strongly scattering media. Given these estimates…
An Analysis of Deep Learning Parameterizations for Ocean Subgrid Eddy Forcing
Cem Gultekin, Adam Subel, Cheng Zhang +5
Due to computational constraints, climate simulations cannot resolve a range of small-scale physical processes, which have a significant impact on the large-scale evolution of the…