46 citations · 263 across the 17 of their papers we have counts for
4 papers · 1 filter
AstroPhot: Fitting Everything Everywhere All at Once in Astronomical Images
Connor Stone, Stephane Courteau, Jean-Charles Cuillandre +3
We present AstroPhot, a fast, powerful, and user-friendly Python based astronomical image photometry solver. AstroPhot incorporates automatic differentiation and GPU (or parallel C…
Population-Level Inference of Strong Gravitational Lenses with Neural Network-Based Selection Correction
Ronan Legin, Connor Stone, Yashar Hezaveh +1
A new generation of sky surveys is poised to provide unprecedented volumes of data containing hundreds of thousands of new strong lensing systems in the coming years. Convolutional…
Realistic galaxy image simulation via score-based generative models
Michael J. Smith, James E. Geach, Ryan A. Jackson +3
We show that a Denoising Diffusion Probabalistic Model (DDPM), a class of score-based generative model, can be used to produce realistic mock images that mimic observations of gala…
Pix2Prof: fast extraction of sequential information from galaxy imagery via a deep natural language 'captioning' model
Michael J. Smith, Nikhil Arora, Connor Stone +2
We present 'Pix2Prof', a deep learning model that can eliminate any manual steps taken when extracting galaxy profiles. We argue that a galaxy profile of any sort is conceptually s…