550 citations · 3.9k across the 60 of their papers we have counts for
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Mapping the Galaxy Color-Star Formation Rate Relation with Manifold Learning and Infrared Image Stacking
Yu-Heng Lin, Daniel Masters, Andreas L. Faisst +7
Modern surveys present us with billions of faint galaxies for which we only have broadband images in 6-8 optical-to-near-infrared (NIR) filters. Galaxy star formation rates (…
Selection of Dwarf Galaxies Hosting AGNs: A Measure of Bias and Contamination using Unsupervised Machine Learning Techniques
Sogol Sanjaripour, Archana Aravindan, Gabriela Canalizo +4
Identifying AGNs in dwarf galaxies is critical for understanding black hole formation but remains challenging due to their low luminosities, low metallicities, and star formation-d…
Denoising Diffusion Probabilistic Model for realistic and fast generated \textit{Euclid}-like data for weak lensing analysis
Diana Scognamiglio, Jake H. Lee, Eric Huff +2
Understanding and mitigating measurement systematics in weak lensing (WL) analysis requires large datasets of realistic galaxies with diverse morphologies and colors. Missions like…
Searching for Quiescent Galaxies over in JWST Surveys Using Manifold Learning
Alexander de la Vega, Mitchell D. Babcock, Bahram Mobasher +5
Quiescent galaxies over are rare and puzzling. They formed and quenched within two billion years and simulations routinely struggle to predict their observed abundances. De…