31 citations · 47 across the 10 of their papers we have counts for
12 papers
SNAD: enabling discovery in the era of big data
Maria Pruzhinskaya, Emille E. O. Ishida, Konstantin Malanchev +8
In the era of wide-field surveys and big data in astronomy, the SNAD team is exploiting the potential of modern datasets for discovering new, unforeseen, or rare astrophysical obje…
The largest ground-based catalogue of M-dwarf flares
A. D. Lavrukhina, B. Demkov, K. Malanchev +2
We present the largest ground-based catalogue of M-dwarf flares to date, comprising 1,229 time-resolved events identified in Zwicky Transient Facility Data Release 17. Using high-c…
What ZTF Saw Where Rubin Looked: Anomaly Hunting in DR23
Maria V. Pruzhinskaya, Anastasia D. Lavrukhina, Timofey A. Semenikhi +7
We present results from the SNAD VIII Workshop, during which we conducted the first systematic anomaly search in the ZTF fields also observed by LSSTComCam during Rubin Scientific…
Signatures to help interpretability of anomalies
Emmanuel Gangler, Emille E. O. Ishida, Matwey V. Kornilov +8
Machine learning is often viewed as a black box when it comes to understanding its output, be it a decision or a score. Automatic anomaly detection is no exception to this rule, an…
Dataset of artefacts for machine learning applications in astronomy
Sreevarsha Sreejith, Maria V. Pruzhinskaya, Alina A. Volnova +8
Accurate photometry in astronomical surveys is challenged by image artefacts, which affect measurements and degrade data quality. Due to the large amount of available data, this ta…
Coniferest: a complete active anomaly detection framework
M. V. Kornilov, V. S. Korolev, K. L. Malanchev +8
We present coniferest, an open source generic purpose active anomaly detection framework written in Python. The package design and implemented algorithms are described. Currently,…
Exploring the Universe with SNAD: Anomaly Detection in Astronomy
Alina A. Volnova, Patrick D. Aleo, Anastasia Lavrukhina +9
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. T…
SNAD catalogue of M-dwarf flares from the Zwicky Transient Facility
A. S. Voloshina, A. D. Lavrukhina, M. V. Pruzhinskaya +11
Most of the stars in the Universe are M spectral class dwarfs, which are known to be the source of bright and frequent stellar flares. In this paper, we propose new approaches to d…
Rainbow: a colorful approach on multi-passband light curve estimation
E. Russeil, K. L. Malanchev, P. D. Aleo +10
We present Rainbow, a physically motivated framework which enables simultaneous multi-band light curve fitting. It allows the user to construct a 2-dimensional continuous surface a…
Automatic detection of plateau phases in light curves of variable stars
Anastasia Lavrukhina, Konstantin Malanchev, Matwey V. Kornilov
Modern astronomical surveys produce millions of light curves of variable sources. These massive data sets challenge the community to create automatic light-curve processing methods…
Performant feature extraction for photometric time series
Anastasia Lavrukhina, Konstantin Malanchev
Astronomy is entering the era of large surveys of the variable sky such as Zwicky Transient Facility (ZTF) and the forthcoming Legacy Survey of Space and Time (LSST) which are inte…
The SNAD Viewer: Everything You Want to Know about Your Favorite ZTF Object
Konstantin Malanchev, Matwey V. Kornilov, Maria V. Pruzhinskaya +9
We describe the SNAD Viewer, a web portal for astronomers which presents a centralized view of individual objects from the Zwicky Transient Facility's (ZTF) data releases, includin…