129 citations · 329 across the 8 of their papers we have counts for
4 papers · 1 filter
DanceCam: atmospheric turbulence mitigation in wide-field astronomical images with short-exposure video streams
Spencer Bialek, Emmanuel Bertin, Sébastien Fabbro +4
We introduce a novel technique to mitigate the adverse effects of atmospheric turbulence on astronomical imaging. Utilizing a video-to-image neural network trained on simulated dat…
StarUnLink: identifying and mitigating signals from communications satellites in stellar spectral surveys
Spencer Bialek, Sara Lucatello, Sebastien Fabbro +2
A relatively new concern for the forthcoming massive spectroscopic sky surveys is the impact of contamination from low earth orbit satellites. Several hundred thousand of these sat…
Assessing the performance of LTE and NLTE synthetic stellar spectra in a machine learning framework
Spencer Bialek, Sébastien Fabbro, Kim A. Venn +3
In the current era of stellar spectroscopic surveys, synthetic spectral libraries are the basis for the derivation of stellar parameters and chemical abundances. In this paper, we…
An Application of Deep Neural Networks in the Analysis of Stellar Spectra
Sebastien Fabbro, Kim Venn, Teaghan O'Briain +4
Spectroscopic surveys require fast and efficient analysis methods to maximize their scientific impact. Here we apply a deep neural network architecture to analyze both SDSS-III APO…