196 citations · 1.3k across the 34 of their papers we have counts for
18 papers · 1 filter
The Variable Universe with the Gaia mission and AI methods
L. Eyer, P. Huijse, N. Chornay +5
The Gaia mission has observed over 2 billion stars repeatedly across the entire sky over 10 years, revealing the many astronomical objects that vary on human timescales from second…
Learning novel representations of variable sources from multi-modal data via autoencoders
P. Huijse, J. De Ridder, L. Eyer +18
Gaia Data Release 3 (DR3) published for the first time epoch photometry, BP/RP (XP) low-resolution mean spectra, and supervised classification results for millions of variable sour…
ALeRCE light curve classifier: Tidal disruption event expansion pack
M. Pavez-Herrera, P. Sánchez-Sáez, L. Hernández-García +9
ALeRCE (Automatic Learning for the Rapid Classification of Events) processes the Zwicky Transient Facility (ZTF) alert stream in preparation for the Vera C. Rubin Observatory, clas…
ATAT: Astronomical Transformer for time series And Tabular data
G. Cabrera-Vives, D. Moreno-Cartagena, N. Astorga +14
The advent of next-generation survey instruments, such as the Vera C. Rubin Observatory and its Legacy Survey of Space and Time (LSST), is opening a window for new research in time…
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…
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…
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…
Alert Classification for the ALeRCE Broker System: The Light Curve Classifier
P. Sánchez-Sáez, I. Reyes, C. Valenzuela +23
We present the first version of the ALeRCE (Automatic Learning for the Rapid Classification of Events) broker light curve classifier. ALeRCE is currently processing the Zwicky Tran…
An Information Theory Approach on Deciding Spectroscopic Follow Ups
Javiera Astudillo, Pavlos Protopapas, Karim Pichara +1
Classification and characterization of variable phenomena and transient phenomena are critical for astrophysics and cosmology. These objects are commonly studied using photometric…
The High Cadence Transient Survey (HITS): Compilation and characterization of light-curve catalogs
Jorge Martínez-Palomera, Francisco Förster, Pavlos Protopapas +12
The High Cadence Transient Survey (HiTS) aims to discover and study transient objects with characteristic timescales between hours and days, such as pulsating, eclipsing and explod…
Enhanced Rotational Invariant Convolutional Neural Network for Supernovae Detection
Esteban Reyes, Pablo A. Estévez, Ignacio Reyes +4
In this paper, we propose an enhanced CNN model for detecting supernovae (SNe). This is done by applying a new method for obtaining rotational invariance that exploits cyclic symme…
Deep Learning for Image Sequence Classification of Astronomical Events
Rodrigo Carrasco-Davis, Guillermo Cabrera-Vives, Francisco Förster +6
We propose a new sequential classification model for astronomical objects based on a recurrent convolutional neural network (RCNN) which uses sequences of images as inputs. This ap…
Robust period estimation using mutual information for multi-band light curves in the synoptic survey era
Pablo Huijse, Pablo A. Estevez, Francisco Forster +5
The Large Synoptic Survey Telescope (LSST) will produce an unprecedented amount of light curves using six optical bands. Robust and efficient methods that can aggregate data from m…
Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases
Pablo Huijse, Pablo A. Estevez, Pavlos Protopapas +2
Time-domain astronomy (TDA) is facing a paradigm shift caused by the exponential growth of the sample size, data complexity and data generation rates of new astronomical sky survey…
A Novel, Fully Automated Pipeline for Period Estimation in the EROS 2 Data Set
Pavlos Protopapas, Pablo Huijse, Pablo A. Estevez +2
We present a new method to discriminate periodic from non-periodic irregularly sampled lightcurves. We introduce a periodic kernel and maximize a similarity measure derived from in…
An Information Theoretic Algorithm for Finding Periodicities in Stellar Light Curves
Pablo Huijse, Pablo A. Estevez, Pavlos Protopapas +2
We propose a new information theoretic metric for finding periodicities in stellar light curves. Light curves are astronomical time series of brightness over time, and are characte…