Related papers: Deep learning interpretability analysis for carbon…

Gaia DR3 provides radial velocities for 33 million stars and spectroscopically derived atmospheric parameters for more than five million targets. When combined with the astrometric data, these allow us to derive orbital and stellar…

The Gaia Data Release 3 (DR3) contains reflectance spectra at visible wavelengths for 60,518 asteroids over the range between 374-1034 nm, representing a large sample that is well suited to studies of asteroid families. We want to assess…

We successfully demonstrate the use of explainable artificial intelligence (XAI) techniques on astronomical datasets in the context of measuring galactic bar lengths. The method consists of training convolutional neural networks on human…

Gaia Data Release 2 (DR2) was used to select a sample of 211 central stars of planetary nebulae (CSPNe) with good quality astrometric measurements, that we refer to as GAPN, Golden Astrometry Planetary Nebulae. Gaia astrometric and…

Extensive astronomical surveys, like those conducted with the {\em Chandra} X-ray Observatory, detect hundreds of thousands of unidentified cosmic sources. Machine learning (ML) methods offer an efficient, probabilistic approach to classify…

Objective. This paper presents an overview of generalizable and explainable artificial intelligence (XAI) in deep learning (DL) for medical imaging, aimed at addressing the urgent need for transparency and explainability in clinical…

Context. The third Gaia Data Release, which includes BP/RP spectra for 219 million sources, has opened a new window in the exploration of the chemical history and evolution of the Milky Way. The wealth of information encapsulated in these…

Precise mass constraints are vital for the characterisation of brown dwarfs and exoplanets. Here we present how the combination of data obtained by Gaia and GRAVITY can help enlarge the sample of substellar companions with measured…

Neutron stars are identified as pulsars, X-ray binary components, central objects of supernovae remnants, or isolated thermally emitting sources, and at distances beyond 120 pc. A population extrapolation suggests 10$^3$ objects within that…

Diffuse interstellar bands (DIBs) are absorption features seen in optical and infrared spectra of stars that are probably caused by large and complex molecules in the ISM. Here we investigate the Galactic distribution and properties of two…

Gaia will obtain astrometry and spectrophotometry for essentially all sources in the sky down to a broad band magnitude limit of G=20, an expected yield of 10^9 stars. Its main scientific objective is to reveal the formation and evolution…

Incorporating style-related objectives into shape design has been centrally important to maximize product appeal. However, stylistic features such as aesthetics and semantic attributes are hard to codify even for experts. As such,…

In the new era of large-scale astronomical surveys, automated methods of analysis and classification of bulk data are a fundamental tool for fast and efficient production of deliverables. This becomes ever more imminent as we enter the Gaia…

Deriving accurate carbon abundance estimates for a wide variety of stars is still complex due to the difficulties in properly measuring it from atomic and molecular lines. The aim of this paper is to analyse the carbon abundance…

Quasars are very important in materializing the reference frame. The excess emission of AGNs (active galactic nuclei) in the mid infrared band can be used to identify quasar candidates. As extremely distant and point like objects, quasars…

The Gaia satellite will observe the positions and velocities of over a billion Milky Way stars. In the early data releases, the majority of observed stars do not have complete 6D phase-space information. In this Letter, we demonstrate the…

We present a novel approach for identifying members of open star clusters using Gaia DR3 data by combining Minimum Spanning Tree (MST) and Gaussian Mixture Model (GMM) techniques. Our method employs a three-step process: initial filtering…

In precision agriculture, one of the most important tasks when exploring crop production is identifying individual plant components. There are several attempts to accomplish this task by the use of traditional 2D imaging, 3D…

Aims. We present an innovative artificial neural network (ANN) architecture, called Generative ANN (GANN), that computes the forward model, that is it learns the function that relates the unknown outputs (stellar atmospheric parameters, in…

Astrometry from Gaia DR3 has produced a sample of $\sim$170,000 Keplerian orbital solutions, with many more anticipated in the next few years. These data have enormous potential to constrain the population of binary stars, giant planets,…