activity
20172026
most citedAnomaly detection in the Zwicky Transient Facility DR3

58 citations · 265 across the 18 of their papers we have counts for

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13 papers · 1 filter

astro-ph.IM2026

Comparing Active Anomaly Detection Frameworks: From Light Curves to Images

Sreevarsha Sreejith, Robert C. Nichol

The increasing volume and complexity of data from modern astronomical surveys are making comprehensive visual inspection increasingly impractical, motivating automated methods for…

astro-ph.IM2025

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…

astro-ph.IM2025

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…

astro-ph.IM2024

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,…

astro-ph.IM2024★ 2 cited

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…

astro-ph.IM2023

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…

astro-ph.IM2023

Point Spread Function Deconvolution Using a Convolutional Autoencoder for Astronomical Applications

Sreevarsha Sreejith, Anže Slosar, Hong Wang

A major issue in optical astronomical image analysis is the combined effect of the instrument's point spread function (PSF) and the atmospheric seeing that blurs images and changes…

astro-ph.IM2022★ 31 cited

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…

astro-ph.IM2022★ 6 cited

Neural Network Based Point Spread Function Deconvolution For Astronomical Applications

Hong Wang, Sreevarsha Sreejith, Yuewei Lin +3

Optical astronomical images are strongly affected by the point spread function (PSF) of the optical system and the atmosphere (seeing) which blurs the observed image. The amount of…

astro-ph.IM2021★ 10 cited

SNAD Transient Miner: Finding Missed Transient Events in ZTF DR4 using k-D trees

P. D. Aleo, K. L. Malanchev, M. V. Pruzhinskaya +7

We report the automatic detection of 11 transients (7 possible supernovae and 4 active galactic nuclei candidates) within the Zwicky Transient Facility fourth data release (ZTF DR4…

astro-ph.IM2020★ 58 cited

Anomaly detection in the Zwicky Transient Facility DR3

K. L. Malanchev, M. V. Pruzhinskaya, V. S. Korolev +11

We present results from applying the SNAD anomaly detection pipeline to the third public data release of the Zwicky Transient Facility (ZTF DR3). The pipeline is composed of 3 stag…

astro-ph.IM2020

Active learning with RESSPECT: Resource allocation for extragalactic astronomical transients

Noble Kennamer, Emille E. O. Ishida, Santiago Gonzalez-Gaitan +12

The recent increase in volume and complexity of available astronomical data has led to a wide use of supervised machine learning techniques. Active learning strategies have been pr…

astro-ph.IM2019★ 46 cited

Active Anomaly Detection for time-domain discoveries

Emille E. O. Ishida, Matwey V. Kornilov, Konstantin L. Malanchev +7

We present the first evidence that adaptive learning techniques can boost the discovery of unusual objects within astronomical light curve data sets. Our method follows an active l…