35 citations · 69 across the 5 of their papers we have counts for
4 papers · 1 filter
Linearized Field Deblending: PSF Photometry for Impatient Astronomers
Christina Hedges, Rodrigo Luger, Jorge Martinez Palomera +2
NASA's Kepler, K2 and TESS missions employ Simple Aperture Photometry (SAP) to derive time-series photometry, where an aperture is estimated for each star, and pixels containing ea…
deepSIP: Linking Type Ia Supernova Spectra to Photometric Quantities with Deep Learning
Benjamin E. Stahl, Jorge Martinez-Palomera, WeiKang Zheng +3
We present {\tt deepSIP} (deep learning of Supernova Ia Parameters), a software package for measuring the phase and -- for the first time using deep learning -- the light-curve sha…
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…
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…