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Researchers have widely used exploratory factor analysis (EFA) to learn the latent structure underlying multivariate data. Rotation and regularised estimation are two classes of methods in EFA that they often use to find interpretable…
Sampling from discrete distributions is a ubiquitous task in machine learning, recently revisited by the emergence of discrete diffusion models. While Langevin algorithms constitute the state of the art for continuous spaces, discrete…
Data mining techniques, including clustering and classification tasks, for the automatic information extraction from large datasets are increasingly demanded in several scientific fields. In particular, in the astrophysical field, large…
We present a fast algorithm to produce light curves of distant stars undergoing microlensing near critical curves. The need of these type of algorithms is motivated by recent observations of microlensing events of distant stars at high…
The Robust Alignment algorithm for the ATLAS silicon detectors is presented. It is an iterative method based on centering residual and overlap residual distributions. Tests on simulated and real data are discussed.
A major issue in optical astronomical image analysis is the combined effect of the instrument's point spread function (PSF) and the atmospheric seeing that blurs images and changes their shape in a way that is band and time-of-observation…
This work addresses the finite-time enclosing control problem where a set of followers are deployed to encircle and rotate around multiple moving targets with a predefined spacing pattern in finite time. A novel distributed and continuous…
Astronomy relies heavily on time domain observations. To maximize the scientific yield of such observations, astronomers must carefully match the observational cadence to the phenomena of interest. This presents significant scheduling…
This textbook provides a systematic treatment of statistical machine learning for astronomical research through the lens of Bayesian inference, developing a unified framework that reveals connections between modern data analysis techniques…
We present an algorithm that computes the multipole coefficients of the galaxy three-point correlation function (3PCF) without explicitly considering triplets of galaxies. Rather, centering on each galaxy in the survey, it expands the…
Modern astronomical surveys such as the Large Synoptic Sky Survey (LSST) promise an unprecedented wealth of discoveries, delivered in the form of ~10 million alerts of time-variable events per night. Astronomers are faced with the daunting…
Astroinformatics is a new impact area in the world of astronomy, occasionally called the final frontier, where several astrophysicists, statisticians and computer scientists work together to tackle various data intensive astronomical…
We test the viability of training machine learning algorithms with synthetic H alpha line profiles to determine the inclination angles of Be stars (the angle between the central B star's rotation axis and the observer's line of sight) from…
Studies of the photometric variability of astronomical sources from ground-based telescopes must overcome atmospheric extinction effects. Differential photometry by reference to an ensemble of reference stars which closely match the target…
We develop an optimization algorithm, using simulated annealing for the quantification of patterns in astronomical data based on techniques developed for robotic vision applications. The methodology falls in the category of cost…
ATLAS is a multipurpose experiment at the LHC. The tracking system of ATLAS, embedded in a 2 T solenoidal field, is composed of different technologies: silicon planar sensors (pixel and microstrips) and drift-tubes. The procedure used to…
Algorithms for accurate localization of pupil centre is essential for gaze tracking in real world conditions. Most of the algorithms fail in real world conditions like illumination variations, contact lenses, glasses, eye makeup, motion…
This paper presents a new algorithm for autonomous multitarget tracking of resident space objects using optical angles-only measurements from a spaceborne observer. To enable autonomous angles-only navigation of spacecraft swarms, an…
We present the DONUTS autoguiding algorithm, designed to fix stellar positions at the sub-pixel level for high-cadence time-series photometry, which is also capable of autoguiding on defocused stars. DONUTS was designed to calculate guide…
Gravitational lens modeling of spatially resolved sources is a challenging inverse problem with many observational constraints and model parameters. We examine established pixel-based source reconstruction algorithms for de-lensing the…