1k citations · 9.5k across the 216 of their papers we have counts for
14 papers · 1 filter
Persistent and occasional: searching for the variable population of the ZTF/4MOST sky using ZTF data release 11
P. Sánchez-Sáez, J. Arredondo, A. Bayo +13
We present a variability, color and morphology based classifier, designed to identify transients, persistently variable, and non-variable sources, from the Zwicky Transient Facilit…
Informative regularization for a multi-layer perceptron RR Lyrae classifier under data shift
Francisco Pérez-Galarce, Karim Pichara, Pablo Huijse +2
In recent decades, machine learning has provided valuable models and algorithms for processing and extracting knowledge from time-series surveys. Different classifiers have been pr…
Deep Drilling in the Time Domain with DECam: Survey Characterization
Melissa L. Graham, Robert A. Knop, Thomas Kennedy +41
This paper presents a new optical imaging survey of four deep drilling fields (DDFs), two Galactic and two extragalactic, with the Dark Energy Camera (DECam) on the 4 meter Blanco…
DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multi-resolution Images
Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes +25
We present DELIGHT, or Deep Learning Identification of Galaxy Hosts of Transients, a new algorithm designed to automatically and in real-time identify the host galaxies of extragal…
Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: a pioneering process of community-focused experimental design
Federica B. Bianco, Željko Ivezić, R. Lynne Jones +43
Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed…
Informative Bayesian model selection for RR Lyrae star classifiers
F. Pérez-Galarce, K. Pichara, P. Huijse +2
Machine learning has achieved an important role in the automatic classification of variable stars, and several classifiers have been proposed over the last decade. These classifier…
The Automatic Learning for the Rapid Classification of Events (ALeRCE) Alert Broker
F. Förster, G. Cabrera-Vives, E. Castillo-Navarrete +37
We introduce the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker, an astronomical alert broker designed to provide a rapid and self--consistent classifica…
Scalable End-to-end Recurrent Neural Network for Variable star classification
Ignacio Becker, Karim Pichara, Márcio Catelan +3
During the last decade, considerable effort has been made to perform automatic classification of variable stars using machine learning techniques. Traditionally, light curves are r…
On the optimal calibration of VVV photometry
Gergely Hajdu, István Dékány, Márcio Catelan +1
Prompted by some inconsistencies in the photometry of the VISTA Variables in the Vía Láctea (VVV) survey, we conduct a revision of the standard calibration procedure of VISTA data…
The Detailed Science Case for the Maunakea Spectroscopic Explorer, 2019 edition
The MSE Science Team, Carine Babusiaux, Maria Bergemann +258
(Abridged) The Maunakea Spectroscopic Explorer (MSE) is an end-to-end science platform for the design, execution and scientific exploitation of spectroscopic surveys. It will unvei…
An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves
Christian Pieringer, Karim Pichara, Márcio Catelán +1
Within the last years, the classification of variable stars with Machine Learning has become a mainstream area of research. Recently, visualization of time series is attracting mor…
A machine learned classifier for RR Lyrae in the VVV survey
Felipe Elorrieta, Susana Eyheramendy, Andrés Jordán +10
Variable stars of RR Lyrae type are a prime tool to obtain distances to old stellar populations in the Milky Way, and one of the main aims of the Vista Variables in the Via Lactea…
VISTA Variables in the Vía Láctea (VVV): Halfway Status and Results
Maren Hempel, Dante Minniti, István Dékány +89
The VISTA Variables in the Vía Láctea (VVV) survey is one of six public ESO surveys, and is now in its 4th year of observing. Although far from being complete, the VVV survey has a…
The Catalina Real-Time Transient Survey (CRTS)
S. G. Djorgovski, A. J. Drake, A. A. Mahabal +9
Catalina Real-Time Transient Survey (CRTS) is a synoptic sky survey uses data streams from 3 wide-field telescopes in Arizona and Australia, covering the total area of ~30,000 deg2…