147 citations · 1.8k across the 70 of their papers we have counts for
27 papers · 1 filter
Multi-Scale Contrastive Attention for Light-Curve Representation Learning
Torsha Majumder, Konstantin Malanchev, Emille E. O. Ishida
Current and next-generation time-domain surveys demand automated techniques capable of analyzing millions of light curves, observed in multiple filters, without relying on exhausti…
SAGUI: SED-based Segmentation of Multi-band Galaxy Images -- Application to JADES in GOODS-South
Rafael S. de Souza, Andressa Wille, Shravya Shenoy +11
We present sagui, a modular framework for the analysis of multi-band imaging data in spatially resolved galaxies, with synergies to integral-field spectroscopy (IFS). Building on t…
A Brief History of Inference in Astronomy
Rafael S. de Souza, Emille E. O. Ishida, Alberto Krone-Martins
In this short review, we trace the evolution of inference in astronomy, highlighting key milestones rather than providing an exhaustive survey. We focus on the shift from classical…
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…
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…
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…
Bayesian multi-band fitting of alerts for kilonovae detection
Biswajit Biswas, Junpeng Lao, Eric Aubourg +4
In the era of multi-messenger astronomy, early classification of photometric alerts from wide-field and high-cadence surveys is a necessity to trigger spectroscopic follow-ups. The…
Finding active galactic nuclei through Fink
Etienne Russeil, Emille E. O. Ishida, Roman Le Montagner +2
We present the Active Galactic Nuclei (AGN) classifier as currently implemented within the Fink broker. Features were built upon summary statistics of available photometric points,…
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…
From Data to Software to Science with the Rubin Observatory LSST
Katelyn Breivik, Andrew J. Connolly, K. E. Saavik Ford +97
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the…
The GRANDMA network in preparation for the fourth gravitational-wave observing run
S. Agayeva, V. Aivazyan, S. Alishov +98
GRANDMA is a world-wide collaboration with the primary scientific goal of studying gravitational-wave sources, discovering their electromagnetic counterparts and characterizing the…
A graph-based spectral classification of Type II supernovae
Rafael S. de Souza, Stephen Thorp, Lluís Galbany +5
Given the ever-increasing number of time-domain astronomical surveys, employing robust, interpretative, and automated data-driven classification schemes is pivotal. Based on graph…
How have astronomers cited other fields in the last decade?
Michele Delli Veneri, Rafael S. de Souza, Alberto Krone-Martins +3
We present a citation pattern analysis between astronomical papers and 13 other disciplines, based on the arXiv database over the past decade (). We analyze 12,600 ast…
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…
Fink: early supernovae Ia classification using active learning
Marco Leoni, Emille E. O. Ishida, Julien Peloton +1
We describe how the Fink broker early supernova Ia classifier optimizes its ML classifications by employing an active learning (AL) strategy. We demonstrate the feasibility of impl…
Debunking Generalization Error or: How I Learned to Stop Worrying and Love My Training Set
Viviana Acquaviva, Chistopher Lovell, Emille Ishida
We aim to determine some physical properties of distant galaxies (for example, stellar mass, star formation history, or chemical enrichment history) from their observed spectra, us…
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…
Fink, a new generation of broker for the LSST community
Anais Möller, Julien Peloton, Emille E. O. Ishida +33
Fink is a broker designed to enable science with large time-domain alert streams such as the one from the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST).…
Periodic Astrometric Signal Recovery through Convolutional Autoencoders
Michele Delli Veneri, Louis Desdoigts, Morgan A. Schmitz +8
Astrometric detection involves a precise measurement of stellar positions, and is widely regarded as the leading concept presently ready to find earth-mass planets in temperate orb…
21st Century Statistical and Computational Challenges in Astrophysics
Eric D. Feigelson, Rafael S. de Souza, Emille E. O. Ishida +1
Modern astronomy has been rapidly increasing our ability to see deeper into the universe, acquiring enormous samples of cosmic populations. Gaining astrophysical insights from thes…
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…
Machine Learning and the future of Supernova Cosmology
Emille E. O. Ishida
Machine Learning methods will play a fundamental role in our ability to optimize the science output from the next generation of large scale surveys. Given the peculiarities of astr…
The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Selection of a performance metric for classification probabilities balancing diverse science goals
A. I. Malz, R. Hložek, T. Allam +22
Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of their underlying physical processes. Ho…
Spatial field reconstruction with INLA: Application to IFU galaxy data
S. González-Gaitán, R. S. de Souza, A. Krone-Martins +4
Astronomical observations of extended sources, such as cubes of integral field spectroscopy (IFS), encode auto-correlated spatial structures that cannot be optimally exploited by s…