550 citations · 3.9k across the 60 of their papers we have counts for
5 papers · 1 filter
The Art of Measuring Physical Parameters in Galaxies: A Critical Assessment of Spectral Energy Distribution Fitting Techniques
Camilla Pacifici, Kartheik G. Iyer, Bahram Mobasher +52
The study of galaxy evolution hinges on our ability to interpret multi-wavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy…
Deblending Galaxies with Generative Adversarial Networks
Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri +6
Deep generative models including generative adversarial networks (GANs) are powerful unsupervised tools in learning the distributions of data sets. Building a simple GAN architectu…
COSMOS-Web: An Overview of the JWST Cosmic Origins Survey
Caitlin M. Casey, Jeyhan S. Kartaltepe, Nicole E. Drakos +82
We present the survey design, implementation, and outlook for COSMOS-Web, a 255 hour treasury program conducted by the James Webb Space Telescope in its first cycle of observations…
A Machine Learning Approach to Predict Missing Flux Densities in Multi-band Galaxy Surveys
Nima Chartab, Bahram Mobasher, Asantha Cooray +21
We present a new method based on information theory to find the optimal number of bands required to measure the physical properties of galaxies with a desired accuracy. As a proof…
COSMOS2020: Manifold Learning to Estimate Physical Parameters in Large Galaxy Surveys
I. Davidzon, K. Jegatheesan, O. Ilbert +16
We present a novel method to estimate galaxy physical properties from spectral energy distributions (SEDs), alternate to template fitting techniques and based on self-organizing ma…