Related papers: Finding rare objects and building pure samples: Pr…
We investigate a sample of 3412 {\it International Celestial Reference Frame} (ICRF3) extragalactic radio-loud sources with accurate positions determined by VLBI in the S/X band, mostly active galactic nuclei (AGN) and quasars, which are…
Most general-purpose classification methods, such as support-vector machine (SVM) and random forest (RF), fail to account for an unusual characteristic of astronomical data: known measurement error uncertainties. In astronomical data, this…
Identifying and removing binary stars from stellar samples is a crucial but complicated task. Regardless of how carefully a sample is selected, some binaries will remain and complicate interpretation of results, especially via flux…
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it is nevertheless plagued by a well-known, well-documented…
Combined studies of variable stars and stellar clusters open great horizons, and they allow us to improve our understanding of stellar cluster formation and stellar evolution. In that prospect, the Gaia mission will provide astrometric,…
We present a method of selecting quasars up to redshift $\approx$ 6 with random forests, a supervised machine learning method, applied to Pan-STARRS1 and WISE data. We find that, thanks to the increasing set of known quasars we can assemble…
We investigate a class of chance-constrained combinatorial optimization problems. Given a pre-specified risk level $\epsilon \in [0,1]$, the chance-constrained program aims to find the minimum cost selection of a vector of binary decisions…
The 100,000 spectra from the 2 degree Field Galaxy Redshift Survey (2dFGRS) in the 100k Public Data Release represent the largest single compilation of galaxy spectra available. By virtue of its sheer size and the properties of the…
Gaussian process regression is a powerful Bayesian nonlinear regression method. Recent research has enabled the capture of many types of observations using non-Gaussian likelihoods. To deal with various tasks in spatial modeling, we benefit…
Observations of clusters suffer from issues such as completeness, projection effects, resolving individual stars and extinction. As such, how accurate are measurements and conclusions are likely to be? Here, we take cluster simulations…
We present a method to identify likely visual binaries in Gaia eDR3 that does not rely on parallax or proper motion. This method utilizes the various PSF sizes of 2MASS/Gaia, where at $<2.5$" two stars may be unresolved in 2MASS but…
This paper presents a generation-based debiasing framework for object detection. Prior debiasing methods are often limited by the representation diversity of samples, while naive generative augmentation often preserves the biases it aims to…
We exploit the spectral archive of the Sloan Digital Sky Survey (SDSS) Data Release 7 to select unusual quasar spectra. The selection method is based on a combination of the power of self-organising maps and the visual inspection of a huge…
Context: Many if not most planetary nebulae (PNe) are now thought to be the outcome of binary evolutionary scenarios. However only a few percent of PNe in the Milky Way are known to host binary systems. The high precision repeated observing…
Context. Quasars are spatially stationary, and they are essential objects in astrometry when defining reference frames. However, the census of quasars is far from complete. Mid-infared colors can be used to find quasar candidates because…
(Abridged) Gaia aims to make a 3-dimensional map of 1,000 million stars in our Milky Way to unravel its kinematical, dynamical, and chemical structure and evolution. Gaia's on-board detection software discriminates stars from spurious…
Nested sampling is often used in Bayesian statistics problems in astronomy. It operates with a set of live points, iteratively replacing the point with the lowest likelihood with a new point of higher likelihood. Each iteration reduces the…
We investigate in detail the effects of sampling on our ability to accurately reconstruct the distribution of galaxies from galaxy surveys. We use a simple probability theory approach, Bayesian classifier theory and Bayesian transition…
Classification and characterization of variable phenomena and transient phenomena are critical for astrophysics and cosmology. These objects are commonly studied using photometric time series or spectroscopic data. Given that many ongoing…
A naive Bayes classifier for identifying Class II YSOs has been constructed and applied to a region of the Northern Galactic Plane containing 8 million sources with good quality Gaia EDR3 parallaxes. The classifier uses the five features:…