We 2024 a.re delighted to announce the conference “Star Formation Across Cosmic Scales: Machine Learning Insights and Applications,” to be held in Budapest, Hungary, between May 13-17, 2024, organised by the consortium of the H2020 funded NEMESIS (Novel Evolutionary Model for the Early Stages of Stars with Intelligent Systems) project.The aim is to highlight and …
Announcement of the SFML Conference from May 13.-17. 2024 Read More »
The most recent Gaia data release (DR3) provides information on an order of magnitude more variable sources than Gaia DR2 in 2018. Among the published additional variability classes is the class of Young Stellar Objects (YSO). We present an extensive work of validation and describe the YSO catalogue in details.
Since the beginning of the last decade the analysis of huge amounts of data is a new challenge that researchers in general have to cope with. This is also true for astronomers and luckily the number of infrared facilities and the amount of data collected by them increased several order of magnitudes, leading us to new discoveries through data mining and knowledge discovery in databases using modern statistical methods, supervised and unsupervised machine learning.
Our current classification scheme for young stellar objects (YSOs) was possible thanks to the advent of the first space-based infrared sky surveys more than 30 years ago. As illustrated in Figure 1, the Classes 0 to III – proposed by Lada (1987, IAUS, 115, 1) and André et al. (1993 ApJ, 206,
