K
Karim Pichara
Researcher at Pontifical Catholic University of Chile
Publications - 49
Citations - 2097
Karim Pichara is an academic researcher from Pontifical Catholic University of Chile. The author has contributed to research in topics: Computer science & Vista Variables in the Via Lactea. The author has an hindex of 18, co-authored 44 publications receiving 2005 citations. Previous affiliations of Karim Pichara include Harvard University & Millennium Institute.
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Astronomical data analysis software and systems
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FATS: Feature Analysis for Time Series
TL;DR: FATS is a Python library which facilitates and standardizes feature extraction for time series data, although the library is generalizable for other uses.
Journal ArticleDOI
The vvv templates project towards an automated classification of vvv light-curves i. Building a database of stellar variability in the near-infrared
Rodolfo Angeloni,Rodolfo Angeloni,R. Contreras Ramos,R. Contreras Ramos,Márcio Catelan,Márcio Catelan,I. Dékány,I. Dékány,F. Gran,F. Gran,Javier Alonso-García,Javier Alonso-García,Maren Hempel,Maren Hempel,Camila Navarrete,Camila Navarrete,H. Andrews,H. Andrews,Antonio Aparicio,Antonio Aparicio,Juan Carlos Beamin,Juan Carlos Beamin,Juan Carlos Beamin,C. Berger,Jura Borissova,Jura Borissova,C. Contreras Peña,A. Cunial,R. de Grijs,Néstor Espinoza,Néstor Espinoza,Susana Eyheramendy,Susana Eyheramendy,C. E. Ferreira Lopes,M. Fiaschi,G. Hajdu,G. Hajdu,J. Han,Krzysztof G. Hełminiak,Krzysztof G. Hełminiak,A. Hempel,Sebastian L. Hidalgo,Sebastian L. Hidalgo,Yoshifusa Ita,Y. B. Jeon,Andrés Jordán,Andrés Jordán,Jungmi Kwon,J. T. Lee,Eric Martin,N. Masetti,Noriyuki Matsunaga,Antonino Milone,Dante Minniti,Lorenzo Morelli,Felipe Murgas,Felipe Murgas,Takumi Nagayama,C. Navarro,C. Navarro,P. Ochner,P. Pérez,Karim Pichara,Karim Pichara,A. Rojas-Arriagada,J. Roquette,R. K. Saito,A. Siviero,J. Sohn,H. I. Sung,Motohide Tamura,Motohide Tamura,R. Tata,L. Tomasella,B. Townsend,B. Townsend,Patricia A. Whitelock +76 more
TL;DR: The VVV Templates Project is described, which describes the construction of this comprehensive database of infrared stellar variability, which will be used as a training-set for the machine-learning algorithms that will automatically classify the light-curves produced by VVv.
Journal ArticleDOI
Photometric classification of quasars from RCS-2 using Random Forest
D. Carrasco,D. Carrasco,L. F. Barrientos,L. F. Barrientos,Karim Pichara,Karim Pichara,Timo Anguita,David Murphy,David Gilbank,Michael D. Gladders,Howard K. C. Yee,Bau-Ching Hsieh,Sebastian Lopez +12 more
TL;DR: In this article, the authors presented a new quasar candidate catalog from the Red-Sequence Cluster Survey 2 (RCS-2), identified solely from photometric information using an automated algorithm suitable for large surveys.
Journal ArticleDOI
Supervised detection of anomalous light curves in massive astronomical catalogs
TL;DR: A new method to automatically discover unknown variable objects in large astronomical catalogs is presented, based on a supervised algorithm that trains a random forest classifier using known variability classes of objects and obtains votes for each of the objects in the training set.