Related papers: Boost recall in QSO selection from highly imbalanc…

Galaxy cluster-scale strong gravitational lensing systems are rare yet valuable tools for investigating the properties of dark matter and dark energy, as well as providing the opportunity to study the distant universe at flux levels and…

We present the results of a programme to search and identify the nature of unusual sources within the All-sky Wide-field Infrared Survey Explorer (WISE) that is based on a machine-learning algorithm for anomaly detection, namely one-class…

We develop a machine learning-based framework to predict the HI content of galaxies using more straightforwardly observable quantities such as optical photometry and environmental parameters. We train the algorithm on z=0-2 outputs from the…

We present results exploring the role that probabilistic deep learning models can play in cosmology from large-scale astronomical surveys through photometric redshift (photo-z) estimation. Photo-z uncertainty estimates are critical for the…

Pulsar candidate sifting is an essential process for discovering new pulsars. It aims to search for the most promising pulsar candidates from an all-sky survey, such as High Time Resolution Universe (HTRU), Green Bank Northern Celestial Cap…

Bright sub-mm galaxies are expected to arise in massive highly-biased haloes, and hence exhibit strong clustering. We argue that a valuable tool for measuring these clustering properties is the cross-correlation of sub-mm galaxies with…

We present a star/galaxy classification for the Southern Photometric Local Universe Survey (S-PLUS), based on a Machine Learning approach: the Random Forest algorithm. We train the algorithm using the S-PLUS optical photometry up to $r$=21,…

In this work, Machine Learning (ML) methods are used to efficiently identify the unassociated sources and the Blazar Candidate of Uncertain types (BCUs) in the Fermi-LAT Third Source Catalog (3FGL). The aims are twofold: 1) to distinguish…

The lensing of background QSOs by foreground galaxies is a powerful probe of the mass density of the Universe and the power spectrum of mass clustering. However, the 2dF QSO survey suggested that a strong anticorrelation effect at g<21 was…

In this Paper we present a clustering analysis of QSOs as a function of luminosity over the redshift range z=0.3-2.9. We use a sample of 10566 QSOs taken from the preliminary data release catalogue of the 2dF QSO Redshift Survey (2QZ). We…

In incremental classification tasks for hyperspectral images, catastrophic forgetting is an unavoidable challenge. While memory recall methods can mitigate this issue, they heavily rely on samples from old categories. This paper proposes a…

We recently started a systematic search of low-energy counterparts of the unidentified gamma-ray sources (UGSs) listed in the Fermi-Large Area Telescope (LAT) First Source Catalog (1FGL) and the Fermi-LAT 2-Year Source Catalog (2FGL).} The…

We search for quasi-stellar objects (QSOs) in a wide area of the south ecliptic pole (SEP) field, which has been and will continue to be intensively explored through various space missions. For this purpose, we obtain deep broadband optical…

This is the first paper in a series aimed at defining a statistically significant sample of QSOs in the range $ 15 < B < 18.75$ and $ 0.3 < z < 2.2$. The selection is carried out using direct plates obtained at the ESO and UK Schmidt…

Context: The Red MSX Source (RMS) survey is a multi-wavelength campaign of follow-up observations of a colour-selected sample of candidate massive young stellar objects (MYSOs) in the galactic plane. This survey is returning the largest…

We present an algorithm for selecting an uniform sample of gravitationally lensed quasar candidates from low-redshift (0.6<z<2.2) quasars brighter than i=19.1 that have been spectroscopically identified in the SDSS. Our algorithm uses…

Machine learning classifiers often stumble over imbalanced datasets where classes are not equally represented. This inherent bias towards the majority class may result in low accuracy in labeling minority class. Imbalanced learning is…

Although the Lambda Cold Dark Matter model is the most accredited cosmological model, information at intermediate redshifts (z) between type Ia Supernovae (z = 2.26) and the Cosmic Microwave Background (z = 1100) is crucial to validate this…

Modern astronomical surveys are producing datasets of unprecedented size and richness, increasing the potential for high-impact scientific discovery. This possibility, coupled with the challenge of exploring a large number of sources, has…

We explore strategies to extract cosmological constraints from a joint analysis of cosmic shear, galaxy-galaxy lensing, galaxy clustering, cluster number counts and cluster weak lensing. We utilize the CosmoLike software to simulate results…