1.4k citations · 15.5k across the 217 of their papers we have counts for
5 papers · 1 filter
As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Elijah P. Mathews, Joel Leja, Joshua S. Speagle +7
Artificial neural network emulators have been demonstrated to be a very computationally efficient method to rapidly generate galaxy spectral energy distributions (SEDs), for parame…
SBI++: Flexible, Ultra-fast Likelihood-free Inference Customized for Astronomical Applications
Bingjie Wang, Joel Leja, V. Ashley Villar +1
Flagship near-future surveys targeting galaxies across cosmic time will soon reveal the processes of galaxy assembly in unprecedented resolution. This creates an immedi…
Monte Carlo Techniques for Addressing Large Errors and Missing Data in Simulation-based Inference
Bingjie Wang, Joel Leja, Ashley Villar +1
Upcoming astronomical surveys will observe billions of galaxies across cosmic time, providing a unique opportunity to map the many pathways of galaxy assembly to an incredibly high…
Hierarchical Bayesian inference of photometric redshifts with stellar population synthesis models
Boris Leistedt, Justin Alsing, Hiranya Peiris +2
We present a Bayesian hierarchical framework to analyze photometric galaxy survey data with stellar population synthesis (SPS) models. Our method couples robust modeling of spectra…
SPECULATOR: Emulating stellar population synthesis for fast and accurate galaxy spectra and photometry
Justin Alsing, Hiranya Peiris, Joel Leja +6
We present SPECULATOR - a fast, accurate, and flexible framework for emulating stellar population synthesis (SPS) models for predicting galaxy spectra and photometry. For emulating…