106 citations · 519 across the 30 of their papers we have counts for
14 papers · 1 filter
Lightstack: A Python Package for Creating Photometric Data Cubes
Andressa Wille, Rafael S. de Souza, Ana L. Chies-Santos +3
Multi-band photometry traces diverse physical processes across a wide range of wavelengths. In recent decades, this field has been driven by the rapid growth of multi-imaging datas…
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…
ELEPHANT: ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients
P. J. Pessi, R. Durgesh, L. Nakazono +11
Context. Transient astronomical events that exhibit no discernible association with a host galaxy are commonly referred to as hostless. These rare phenomena are associated with ext…
Applications of AI in Astronomy
S. G. Djorgovski, A. A. Mahabal, M. J. Graham +2
We provide a brief, and inevitably incomplete overview of the use of Machine Learning (ML) and other AI methods in astronomy, astrophysics, and cosmology. Astronomy entered the big…
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…
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…
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…
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…
Optimizing spectroscopic follow-up strategies for supernova photometric classification with active learning
E. E. O. Ishida, R. Beck, S. Gonzalez-Gaitan +10
We report a framework for spectroscopic follow-up design for optimizing supernova photometric classification. The strategy accounts for the unavoidable mismatch between spectroscop…
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…
Using gamma regression for photometric redshifts of survey galaxies
J. Elliott, R. S. de Souza, A. Krone-Martins +3
Machine learning techniques offer a plethora of opportunities in tackling big data within the astronomical community. We present the set of Generalized Linear Models as a fast alte…
The Overlooked Potential of Generalized Linear Models in Astronomy-II: Gamma regression and photometric redshifts
J. Elliott, R. S. de Souza, A. Krone-Martins +3
Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions abo…