Related papers: Using cGANs for Anomaly Detection: Identifying Ast…

We targeted with deep NOEMA observations the [CII]158$\mu$m emission of three JWST-discovered AGN at z>6. Two of them have the typical features of Little Red Dots (LRDs), while the third one is a blue, extended, Type I AGN. We do not…

In this paper, we investigate algorithms for anomaly detection. Previous anomaly detection methods focus on modeling the distribution of non-anomalous data provided during training. However, this does not necessarily ensure the correct…

JWST spectroscopy has discovered a population of $z \gtrsim 3.5$ galaxies with broad Balmer emission lines, and narrow forbidden lines, that are consistent with hosting active galactic nuclei (AGN). Many of these systems, now known as…

The goal of this paper is to investigate the physical nature of galaxies in the redshift range $0.02<z<0.15$ that have strong excess emission at mid-IR wavelengths and to determine whether they host a population of accreting black holes…

We present the reduced images and multi-wavelength catalog of the first JWST NIRCam extra-galactic observations from the GLASS Early Release Science Program, obtained as coordinated parallels of the NIRISS observations of the Abell 2744…

Generative adversarial networks are a promising tool for image generation in the astronomy domain. Of particular interest are conditional generative adversarial networks (cGANs), which allow you to divide images into several classes…

JWST imaging of the rich galaxy cluster Abell 2744 at $z=0.308$ has been used by the UNCOVER team (Bezanson et al. 2022) to construct mosaic images in the NIRCAM filters. The exceptionally deep images in the ($F115W$, $F150W$, $F200W$)…

The radio observation of 21\,cm-line signal from the Epoch of Reionization (EoR) enables us to explore the evolution of galaxies and intergalactic medium in the early universe. However, the detection and imaging of the 21\,cm-line signal…

The nature of the interaction between active galactic nuclei (AGNs) and their host galaxies remains an unsolved question. Therefore, conducting an AGN census is valuable to AGN research. Nevertheless, a significant fraction of AGNs are…

Conditional Generative Adversarial Networks (cGANs) extend the standard unconditional GAN framework to learning joint data-label distributions from samples, and have been established as powerful generative models capable of generating…

Quasars with extremely red infrared-to-optical colours are an interesting population that can test ideas about quasar evolution as well as orientation, obscuration and geometric effects in the so-called AGN unified model. To identify such a…

In this work, we spectroscopically select narrow-line AGNs (NLAGNs) among the ~300 publicly available medium-resolution spectra of the Cosmic Evolution Early Release Science Survey (CEERS). Using both traditional and newly identified…

In this paper we address the abnormality detection problem in crowded scenes. We propose to use Generative Adversarial Nets (GANs), which are trained using normal frames and corresponding optical-flow images in order to learn an internal…

We present a search for extremely red, dust-obscured, $z>7$ galaxies with $\textit{JWST}$/NIRCam+MIRI imaging over the first 20 arcmin$^2$ of publicly-available Cycle 1 data from the COSMOS-Web, CEERS, and PRIMER surveys. Based on their red…

A wealth of extragalactic populations completely missed at UV-optical wavelengths has been identified in the last decade, combining the deepest HST and Spitzer observations. These dark sources are thought to be very dusty and star-forming…

We report the serendipitous discovery of an extended stellar halo surrounding the low-mass galaxy Ark 227 ($M_\ast=5\times10^9 M_\odot$; d=35 Mpc) in deep JWST NIRCam imaging from the Blue Jay Survey. The F200W-F444W color provides robust…

Anomaly detection has wide applications in machine intelligence but is still a difficult unsolved problem. Major challenges include the rarity of labeled anomalies and it is a class highly imbalanced problem. Traditional unsupervised…

This study presents an adversarial method for anomaly detection in real-world applications, leveraging the power of generative adversarial neural networks (GANs) through cycle consistency in reconstruction error. Previous methods suffer…

The goal of anomaly detection is to identify anomalous samples from normal ones. In this paper, a small number of anomalies are assumed to be available at the training stage, but they are assumed to be collected only from several anomaly…

Radio surveys are widely used to study active galactic nuclei. Radio interferometric observations typically trade-off surface brightness sensitivity for angular resolution. Hence, observations using a wide range of baseline lengths are…