62 citations · 92 across the 7 of their papers we have counts for
8 papers
CHAMPS: The COSMOS High-Redshift ALMA-MIRI Population Survey - A New Census of the Dusty Early Universe
Andreas L. Faisst, Felix Martinez, Jeyhan S. Kartaltepe +86
Understanding how dust forms and evolves over cosmic time is a key open problem in extragalactic astrophysics. Galaxies in the early Universe were once thought to be mostly dust-po…
AGN-DB: A Unified Multi-Wavelength Database of Active Galactic Nuclei
Alessandro Peca, Nico Cappelluti, C. Megan Urry +29
We present the Active Galactic Nuclei Database (AGN-DB), a comprehensive, multi-wavelength catalog compiled from more than 100 publicly available AGN catalogs and samples released…
Using Machine Learning to Determine Morphologies of AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey
Chuan Tian, C. Megan Urry, Aritra Ghosh +9
We present a machine-learning framework to accurately characterize morphologies of Active Galactic Nucleus (AGN) host galaxies within . We first use PSFGAN to decouple host ga…
Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey
Aritra Ghosh, C. Megan Urry, Aayush Mishra +10
We use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for million galaxies in the Hyper Supr…
On the cosmic evolution of AGN obscuration and the X-ray luminosity function: XMM-Newton and Chandra spectral analysis of the 31.3 deg Stripe 82X
Alessandro Peca, Nico Cappelluti, Meg Urry +11
We present X-ray spectral analysis of XMM and Chandra observations in the 31.3 deg Stripe-82X (S82X) field. Of the 6181 X-ray sources in this field, we analyze a sample of 2937…
GaMPEN: A Machine Learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters
Aritra Ghosh, C. Megan Urry, Amrit Rau +11
We introduce a novel machine learning framework for estimating the Bayesian posteriors of morphological parameters for arbitrarily large numbers of galaxies. The Galaxy Morphology…
Compositional Graphical Lasso Resolves the Impact of Parasitic Infection on Gut Microbial Interaction Networks in a Zebrafish Model
Chuan Tian, Duo Jiang, Austin Hammer +2
Understanding how microbes interact with each other is key to revealing the underlying role that microorganisms play in the host or environment and to identifying microorganisms as…
Reference-Invariant Inverse Covariance Estimation with Application to Microbial Network Recovery
Chuan Tian, Duo Jiang, Yuan Jiang
The interactions between microbial taxa in microbiome data has been under great research interest in the science community. In particular, several methods such as SPIEC-EASI, gCoda…