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

Current gravitational wave (GW) detections rely on the existence of libraries of theoretical waveforms. Consequently, finding new physics with GWs requires libraries of non-standard models, which are computationally demanding. We discuss…

Recent advances in Generative Adversarial Networks (GANs) have led to the creation of realistic-looking digital images that pose a major challenge to their detection by humans or computers. GANs are used in a wide range of tasks, from…

We analyze eight spectroscopically confirmed Little Red Dots (LRDs) at redshifts $z = 5.1-8.7$ with JWST/NIRCam, NIRSpec, and MIRI data. The LRDs have red NIRCam colors, F150W-F444W $>$ 1, but flat NIRCam-MIRI colors, $-0.5 < \mathrm{F444W…

Red supergiants (RSGs) are crucial for studying the properties and evolution of massive stars. It is representative to conduct a census of RSGs across the Local Group, which spans a broad metallicity range. However, identifying RSGs in…

Time series anomalies can offer information relevant to critical situations facing various fields, from finance and aerospace to the IT, security, and medical domains. However, detecting anomalies in time series data is particularly…

We study 87 Extremely Red Objects (EROs), selected both to have color redder than R-[3.6] = 4.0, and to have confirmed spectroscopic redshifts. Together, these two constraints result in this sample populating a fairly narrow redshift range…

We utilize the CLASH (Cluster Lensing And Supernova survey with Hubble) observations of 25 clusters to search for extreme emission-line galaxies (EELGs). The selections are carried out in two central bands: F105W (Y105) and F125W (J125), as…

Over the last two decades, a lot of work has been done in improving network security, particularly in intrusion detection systems (IDS) and anomaly detection. Machine learning solutions have also been employed in IDSs to detect known and…

We explore spectroscopic and photometric methods for identifying high-redshift galaxies containing an Active Galactic Nucleus (AGN) with JWST observations. After demonstrating the limitations of standard optical methods, which appear…

We present predictions for the clustering of Extremely Red Objects (EROs) in a \Lambda cold dark matter Universe, using a semi-analytical galaxy formation model in combination with a cosmological N-body simulation. EROs are red, massive…

We use Generative Adversarial Networks (GANs) to design a class conditional label noise (CCN) robust scheme for binary classification. It first generates a set of correctly labelled data points from noisy labelled data and 0.1% or 1% clean…

In conditional Generative Adversarial Networks (cGANs), when two different initial noises are concatenated with the same conditional information, the distance between their outputs is relatively smaller, which makes minor modes likely to…

Insider threats are the cyber attacks from within the trusted entities of an organization. Lack of real-world data and issue of data imbalance leave insider threat analysis an understudied research area. To mitigate the effect of skewed…

Anomaly detection has become an indispensable tool for modern society, applied in a wide range of applications, from detecting fraudulent transactions to malignant brain tumours. Over time, many anomaly detection techniques have been…

Subject to intricate environmental variables, the precise classification of jamming signals holds paramount significance in the effective implementation of anti-jamming strategies within communication systems. In light of this imperative,…

Anomaly detection is often considered a challenging field of machine learning due to the difficulty of obtaining anomalous samples for training and the need to obtain a sufficient amount of training data. In recent years, autoencoders have…

Anomaly detection in time series data, to identify points that deviate from normal behaviour, is a common problem in various domains such as manufacturing, medical imaging, and cybersecurity. Recently, Generative Adversarial Networks (GANs)…

We present the results of sub-mm, mm (850 um, 450 um and 1250 um) and radio (1.4 and 4.8 GHz) continuum observations of a sample of 27 K-selected Extremely Red Objects, or EROs, (14 of which form a complete sample with K < 20 and I-K > 5)…

We present new lensing frequency estimates for existing and forthcoming deep near-infrared surveys, including those from JWST and VISTA. The estimates are based on the JAdes extraGalactic Ultradeep Artificial Realisations (JAGUAR) galaxy…

Observations with the James Webb Space Telescope (JWST) reveal a previously unseen population of compact red objects, known as ``little red dots`` (LRDs). We study a new photometrically selected sample of 124 LRDs in the redshift range $z$…