258 citations · 1.1k across the 19 of their papers we have counts for
5 papers · 1 filter
DIGS: Deep Inference of Galaxy Spectra with Neural Posterior Estimation
Gourav Khullar, Brian Nord, Aleksandra Ciprijanovic +2
With the advent of billion-galaxy surveys with complex data, the need of the hour is to efficiently model galaxy spectral energy distributions (SEDs) with robust uncertainty quanti…
Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference
Jason Poh, Ashwin Samudre, Aleksandra Ćiprijanović +4
Current ground-based cosmological surveys, such as the Dark Energy Survey (DES), are predicted to discover thousands of galaxy-scale strong lenses, while future surveys, such as th…
Identification of Galaxy-Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning
E. A. Zaborowski, A. Drlica-Wagner, F. Ashmead +88
We perform a search for galaxy-galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local V…
Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference
Moonzarin Reza, Yuanyuan Zhang, Brian Nord +3
Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulati…
TDCOSMO. IX. Systematic comparison between lens modelling software programs: time delay prediction for WGD 2038-4008
A. J. Shajib, K. C. Wong, S. Birrer +15
The importance of alternative methods for measuring the Hubble constant, such as time-delay cosmography, is highlighted by the recent Hubble tension. It is paramount to thoroughly…