Search Results - "Pichara, K."

Scalable end-to-end recurrent neural network for variable star classification by Becker, I, Pichara, K, Catelan, M, Protopapas, P, Aguirre, C, Nikzat, F

“…ABSTRACT During the last decade, considerable effort has been made to perform automatic classification of variable stars using machine-learning techniques…”
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Deep multi-survey classification of variable stars by Aguirre, C, Pichara, K, Becker, I

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Semi-supervised classification and clustering analysis for variable stars by Pantoja, R, Catelan, M, Pichara, K, Protopapas, P

“…ABSTRACT The immense amount of time series data produced by astronomical surveys has called for the use of machine learning algorithms to discover and classify…”
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Streaming classification of variable stars by Zorich, L, Pichara, K, Protopapas, P

“…ABSTRACT In the last years, automatic classification of variable stars has received substantial attention. Using machine learning techniques for this task has…”
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Informative Bayesian model selection for RR Lyrae star classifiers by Pérez-Galarce, F, Pichara, K, Huijse, P, Catelan, M, Mery, D

“…ABSTRACT Machine learning has achieved an important role in the automatic classification of variable stars, and several classifiers have been proposed over the…”
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A Broadband Vibration-Based Energy Harvester Using an Array of Piezoelectric Beams Connected by Springs by Meruane, V., Pichara, K.

“…Piezoelectric cantilevered beams have been widely used asvibration-based energy harvesters. Nevertheless, these deviceshave a narrow frequency band and if the…”
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The VISTA Variables in the Vía Láctea infrared variability catalogue (VIVA-I) by Ferreira Lopes, C E, Cross, N J G, Catelan, M, Minniti, D, Hempel, M, Lucas, P W, Angeloni, R, Jablonsky, F, Braga, V F, Leão, I C, Herpich, F R, Alonso-García, J, Papageorgiou, A, Pichara, K, Saito, R K, Bradley, A J, Beamin, J C, Cortés, C, De Medeiros, J R, Russell, Christopher M P

“…ABSTRACT High extinction and crowding create a natural limitation for optical surveys towards the central regions of the Milky Way, where the gas and dust are…”
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An improved quasar detection method in EROS-2 and MACHO LMC data sets by Pichara, K., Protopapas, P., Kim, D.-W., Marquette, J.-B., Tisserand, P.

“…We present a new classification method for quasar identification in the EROS-2 and MACHO data sets based on a boosted version of a random forest classifier. We…”
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Understanding Learning Resources Metadata for Primary and Secondary Education by Peralta, M., Alarcon, R., Pichara, K., Mery, T., Cano, F., Bozo, J.

“…Educational resources can be easily found on the Web. Most search engines base their algorithms on a resource's text or popularity, requiring teachers to…”
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Informative regularization for a multi-layer perceptron RR Lyrae classifier under data shift by Pérez-Galarce, F., Pichara, K., Huijse, P., Catelan, M., Mery, D.

“…In recent decades, machine learning has provided valuable models and algorithms for processing and extracting knowledge from time-series surveys. Different…”
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Astronomical data analysis software and systems by Lorente, N., Pichara, K.

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An improved quasar detection method in EROS-2 and MACHO LMC data sets: Quasar detection method in EROS-2 and MACHO by Pichara, K., Protopapas, P., Kim, D.-W., Marquette, J.-B., Tisserand, P.

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Semi-Supervised Classification and Clustering Analysis for Variable Stars by Pantoja, R, Catelan, M, Pichara, K, Protopapas, P

“…The immense amount of time series data produced by astronomical surveys has called for the use of machine learning algorithms to discover and classify several…”
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Informative Bayesian model selection for RR Lyrae star classifiers by Pérez-Galarce, F, Pichara, K, Huijse, P, Catelan, M, Mery, D

“…Machine learning has achieved an important role in the automatic classification of variable stars, and several classifiers have been proposed over the last…”
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New variable Stars from the Photographic Archive: Semi-automated Discoveries, Attempts of Automatic Classification, and the New Field 104 Her by Antipin, S. V, Becker, I, Belinski, A. A, Kolesnikova, D. M, Pichara, K, Samus, N. N, Sokolovsky, K. V, Zharova, A. V, Zubareva, A. M

“…Using 172 plates taken with the 40-cm astrograph of the Sternberg Astronomical Institute (Lomonosov Moscow University) in 1976-1994 and digitized with the…”
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The VVV Infrared Variability Catalog (VIVA-I) by Lopes, C. E. Ferreira, Cross, N. J. G, Catelan, M, Minniti, D, Hempel, M, Lucas, P. W, Angeloni, R, Jablonsky, F, Braga, V. F, Leao, I. C, Herpich, F. R, Alonso-Garcia, J, Papageorgiou, A, Pichara, K, Saito, R. K, Bradley, A, Beamin, J. C, Cortes, C, De Medeiros, J. R, Russell, Christopher. M. P

“…Thanks to the VISTA Variables in the Via Lactea (VVV) ESO Public Survey it is now possible to explore a large number of objects in those regions. This paper…”
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Photometric Classification of quasars from RCS-2 using Random Forest by Carrasco, D, Barrientos, L. F, Pichara, K, Anguita, T, Murphy, D. N. A, Gilbank, D. G, Gladders, M. D, Yee, H. K. C, Hsieh, B. C, López, S

“…A&A 584, A44 (2015) Aims. Construction of a new quasar candidate catalog from the Red-Sequence Cluster Survey 2 (RCS-2), identified solely from photometric…”
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The VVV Templates Project. Towards an Automated Classification of VVV Light-Curves. I. Building a database of stellar variability in the near-infrared by Angeloni, R, Ramos, R. Contreras, Catelan, M, Dékány, I, Gran, F, Alonso-García, J, Hempel, M, Navarrete, C, Andrews, H, Aparicio, A, Beamín, J. C, Berger, C, Borissova, J, Peña, C. Contreras, Cunial, A, de Grijs, R, Espinoza, N, Eyheramendy, S, Lopes, C. E. Ferreira, Fiaschi, M, Hajdu, G, Han, J, Hełminiak, K. G, Hempel, A, Hidalgo, S. L, Ita, Y, Jeon, Y. -B, Jordán, A, Kwon, J, Lee, J. T, Martín, E. L, Masetti, N, Matsunaga, N, Milone, A. P, Minniti, D, Morelli, L, Murgas, F, Nagayama, T, Navarro, C, Ochner, P, Pérez, P, Pichara, K, Rojas-Arriagada, A, Roquette, J, Saito, R. K, Siviero, A, Sohn, J, Sung, H. -I, Tamura, M, Tata, R, Tomasella, L, Townsend, B, Whitelock, P

“…A&A 567, A100 (2014) Context. The Vista Variables in the V\'ia L\'actea (VVV) ESO Public Survey is a variability survey of the Milky Way bulge and an adjacent…”
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Stellar Variability in the VVV survey by Catelan, M, Minniti, D, Lucas, P. W, Dékány, I, Saito, R. K, Angeloni, R, Alonso-García, J, Hempel, M, Helminiak, K, Jordán, A, Ramos, R. Contreras, Navarrete, C, Beamín, J. C, Rojas, A. F, Gran, F, Lopes, C. E. Ferreira, Peña, C. Contreras, Kerins, E, Huckvale, L, Rejkuba, M, Cohen, R, Mauro, F, Borissova, J, Amigo, P, Eyheramendy, S, Pichara, K, Espinoza, N, Navarro, C, Hajdu, G, Espinoza, D. N. Calderón, Muro, G. A, Andrews, H, Motta, V, Kurtev, R, Emerson, J. P, Bidin, C. Moni, Chené, A. -N

“…The Vista Variables in the V\'ia L\'actea (VVV) ESO Public Survey is an ongoing time-series, near-infrared (IR) survey of the Galactic bulge and an adjacent…”
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The Vista Variables in the Via Lactea (VVV) ESO Public Survey: Current Status and First Results by Catelan, M, Minniti, D, Lucas, P. W, Alonso-Garcia, J, Angeloni, R, Beamin, J. C, Bonatto, C, Borissova, J, Contreras, C, Cross, N, Dekany, I, Emerson, J. P, Eyheramendy, S, Geisler, D, Gonzalez-Solares, E, Helminiak, K. G, Hempel, M, Irwin, M. J, Ivanov, V. D, Jordan, A, Kerins, E, Kurtev, R, Mauro, F, Bidin, C. Moni, Navarrete, C, Perez, P, Pichara, K, Read, M, Rejkuba, M, Saito, R. K, Sale, S. E, Toledo, I

“…Vista Variables in the Via Lactea (VVV) is an ESO Public Survey that is performing a variability survey of the Galactic bulge and part of the inner disk using…”
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