activity
20112020
most citedA Review of Feature Selection Methods Based on Mutual Information

1.3k citations · 2.5k across the 15 of their papers we have counts for

collaborators

14 papers

astro-ph.IM2020★ 196 cited

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…

astro-ph.IM2020★ 135 cited

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…

astro-ph.EP2020★ 15 cited

Asteroids' Size Distribution and Colors from HiTS

J. Peña, C. Fuentes, F. Förster +8

We report the observations of solar system objects during the 2015 campaign of the High cadence Transient Survey (HiTS). We found 5740 bodies (mostly Main Belt asteroids), 1203 of…

astro-ph.HE2018★ 166 cited

The delay of shock breakout due to circumstellar material seen in most Type II Supernovae

F. Förster, T. J. Moriya, J. C. Maureira +35

Type II supernovae (SNe) originate from the explosion of hydrogen-rich supergiant massive stars. Their first electromagnetic signature is the shock breakout, a short-lived phenomen…

astro-ph.IM2018★ 10 cited

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…

astro-ph.IM2018★ 47 cited

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…

astro-ph.IM2017★ 35 cited

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…

astro-ph.IM2017★ 122 cited

Deep-HiTS: Rotation Invariant Convolutional Neural Network for Transient Detection

Guillermo Cabrera-Vives, Ignacio Reyes, Francisco Förster +2

We introduce Deep-HiTS, a rotation invariant convolutional neural network (CNN) model for classifying images of transients candidates into artifacts or real sources for the High ca…

astro-ph.IM2015★ 85 cited

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…

cs.LG2015★ 1.3k cited

A Review of Feature Selection Methods Based on Mutual Information

Jorge R. Vergara, Pablo A. Estévez

In this work we present a review of the state of the art of information theoretic feature selection methods. The concepts of feature relevance, redundance and complementarity (syne…

cs.LG2015★ 132 cited

A review of learning vector quantization classifiers

David Nova, Pablo A. Estevez

In this work we present a review of the state of the art of Learning Vector Quantization (LVQ) classifiers. A taxonomy is proposed which integrates the most relevant LVQ approaches…

astro-ph.IM2014★ 10 cited

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…

astro-ph.IM2012★ 40 cited

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…

cs.IT2011★ 24 cited

Period Estimation in Astronomical Time Series Using Slotted Correntropy

Pablo Huijse, Pablo A. Estévez, Pablo Zegers +2

In this letter, we propose a method for period estimation in light curves from periodic variable stars using correntropy. Light curves are astronomical time series of stellar brigh…