196 citations · 901 across the 8 of their papers we have counts for
7 papers
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…
Alert Classification for the ALeRCE Broker System: The Real-time Stamp Classifier
Rodrigo Carrasco-Davis, Esteban Reyes, Camilo Valenzuela +20
We present a real-time stamp classifier of astronomical events for the ALeRCE (Automatic Learning for the Rapid Classification of Events) broker. The classifier is based on a convo…
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…
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…
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…