10 citations · 14 across the 9 of their papers we have counts for
11 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…
Supernova scores for active anomaly detection
Semenikhin T. A., Kornilov M. V., Pruzhinskaya M. V. +3
Large time-domain sky surveys generate extensive multi-year catalogs of light curves in which scientifically valuable transients, such as supernovae (SNe), are vastly outnumbered b…
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,…
Superluminous supernova search with PineForest
T. Majumder, M. V. Pruzhinskaya, E. E. O. Ishida +3
The advent of wide-field astronomical surveys has made available large and complex data sets. However, the process of discovery and interpretation of each potentially new astronomi…
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…
Reduction of supernova light curves by vector Gaussian processes
Matwey V. Kornilov, T. A. Semenikhin, M. V. Pruzhinskaya
Bolometric light curves play an important role in understanding the underlying physics of various astrophysical phenomena, as they allow for a comprehensive modeling of the event a…