51 citations · 507 across the 30 of their papers we have counts for
16 papers · 1 filter
Multiband Embeddings of Light Curves
I. Becker, P. Protopapas, M. Catelan +1
In this work, we propose a novel ensemble of recurrent neural networks (RNNs) that considers the multiband and non-uniform cadence without having to compute complex features. Our p…
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…
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…
Classifying CMB time-ordered data through deep neural networks
Felipe Rojas, Loïc Maurin, Rolando Dünner +1
The Cosmic Microwave Background (CMB) has been measured over a wide range of multipoles. Experiments with arc-minute resolution like the Atacama Cosmology Telescope (ACT) have cont…
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…
Streaming Classification of Variable Stars
Lukas Zorich, Karim Pichara, Pavlos Protopapas
In the last years, automatic classification of variable stars has received substantial attention. Using machine learning techniques for this task has proven to be quite useful. Typ…