129 citations · 329 across the 8 of their papers we have counts for
8 papers
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…
The Pristine survey -- XII: Gemini-GRACES chemo-dynamical study of newly discovered extremely metal-poor stars in the Galaxy
Collin L. Kielty, Kim A. Venn, Federico Sestito +16
High-resolution optical spectra of 30 metal-poor stars selected from the \Pristine\ survey are presented, based on observations taken with the Gemini Observatory GRACES spectrograp…
Interpreting Stellar Spectra with Unsupervised Domain Adaptation
Teaghan O'Briain, Yuan-Sen Ting, Sébastien Fabbro +3
We discuss how to achieve mapping from large sets of imperfect simulations and observational data with unsupervised domain adaptation. Under the hypothesis that simulated and obser…
Cycle-StarNet: Bridging the gap between theory and data by leveraging large datasets
Teaghan O'Briain, Yuan-Sen Ting, Sébastien Fabbro +3
The advancements in stellar spectroscopy data acquisition have made it necessary to accomplish similar improvements in efficient data analysis techniques. Current automated methods…
The Pristine survey X: a large population of low-metallicity stars permeates the Galactic disk
Federico Sestito, Nicolas F. Martin, Else Starkenburg +26
The orbits of the least chemically enriched stars open a window on the formation of our Galaxy when it was still in its infancy. The common picture is that these low-metallicity st…
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…