Exploring the Universe with SNAD: Anomaly Detection in Astronomy
Instrumentation and Methods for Astrophysics
2024-10-25 v1 Human-Computer Interaction
Machine Learning
Abstract
SNAD is an international project with a primary focus on detecting astronomical anomalies within large-scale surveys, using active learning and other machine learning algorithms. The work carried out by SNAD not only contributes to the discovery and classification of various astronomical phenomena but also enhances our understanding and implementation of machine learning techniques within the field of astrophysics. This paper provides a review of the SNAD project and summarizes the advancements and achievements made by the team over several years.
Cite
@article{arxiv.2410.18875,
title = {Exploring the Universe with SNAD: Anomaly Detection in Astronomy},
author = {Alina A. Volnova and Patrick D. Aleo and Anastasia Lavrukhina and Etienne Russeil and Timofey Semenikhin and Emmanuel Gangler and Emille E. O. Ishida and Matwey V. Kornilov and Vladimir Korolev and Konstantin Malanchev and Maria V. Pruzhinskaya and Sreevarsha Sreejith},
journal= {arXiv preprint arXiv:2410.18875},
year = {2024}
}
Comments
14 pages, 4 figures