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Spencer Bialek
Spencer Bialek
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An application of deep learning in the analysis of stellar spectra
S Fabbro, KA Venn, T O'Briain, S Bialek, CL Kielty, F Jahandar, S Monty
Monthly Notices of the Royal Astronomical Society 475 (3), 2978-2993, 2018
832018
The Pristine survey–X. A large population of low-metallicity stars permeates the Galactic disc
F Sestito, NF Martin, E Starkenburg, A Arentsen, RA Ibata, N Longeard, ...
Monthly Notices of the Royal Astronomical Society: Letters 497 (1), L7-L12, 2020
442020
The Pristine survey–XII. Gemini-GRACES chemo-dynamical study of newly discovered extremely metal-poor stars in the Galaxy
CL Kielty, KA Venn, F Sestito, E Starkenburg, NF Martin, DS Aguado, ...
Monthly Notices of the Royal Astronomical Society 506 (1), 1438-1461, 2021
162021
Cycle-StarNet: Bridging the Gap between Theory and Data by Leveraging Large Data Sets
T O’Briain, YS Ting, S Fabbro, MY Kwang, K Venn, S Bialek
The Astrophysical Journal 906 (2), 130, 2021
132021
Assessing the performance of LTE and NLTE synthetic stellar spectra in a machine learning framework
S Bialek, S Fabbro, KA Venn, N Kumar, T O’Briain, KM Yi
Monthly Notices of the Royal Astronomical Society 498 (3), 3817-3834, 2020
82020
A 3D printed modular phantom for quality assurance of image‐guided small animal irradiators: Design, imaging experiments, and Monte Carlo simulations
DY Breitkreutz, S Bialek, B Vojnovic, A Kavanagh, CD Johnstone, ...
Medical Physics 46 (5), 2015-2024, 2019
32019
Starnet: A deep learning analysis of infrared stellar spectra
CL Kielty, S Bialek, S Fabbro, KA Venn, T O'Briain, F Jahandar, S Monty
Software and cyberinfrastructure for astronomy v 10707, 814-824, 2018
32018
Interpreting Stellar Spectra with Unsupervised Domain Adaptation
T O'Briain, YS Ting, S Fabbro, KM Yi, K Venn, S Bialek
arXiv preprint arXiv:2007.03112, 2020
12020
An Application of Deep Neural Networks in the Analysis of Stellar Spectra
S Fabbro, K Venn, T O'Briain, S Bialek, C Kielty, F Jahandar, S Monty
arXiv preprint arXiv:1709.09182, 2017
12017
Stellar Parameters with Deep Learning
S Fabbro, K Venn, T O'Briain, S Bialek, C Kielty, F Jahandar, S Monty
Astronomical Data Analysis Software and Systems XXVII 522, 393, 2020
2020
Deep learning analyses of synthetic spectral libraries with an application to the Gaia-ESO database
S Bialek
2019
3D Printed Phantom for MicroCT Imaging QA
S Bialek, B Vojanovic, A Kavanagh, C Johnstone, T Kanesalingam, ...
MEDICAL PHYSICS 45 (6), E421-E421, 2018
2018
StarNet: An application of deep learning in the analysis of stellar spectra
C Kielty, S Bialek, S Fabbro, K Venn, T O'Briain, F Jahandar, S Monty
American Astronomical Society Meeting Abstracts# 232 232, 223.09, 2018
2018
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