The Citing articles tool gives a list of articles citing the current article. The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
This article has been cited by the following article(s):
Classification of Exoplanetary Light Curves Using Artificial Intelligence
Leticia Flores-Pulido, Liliana Ibeth Barbosa-Santillán, Ma. Teresa Orozco-Aguilera and Bertha Patricia Guzman-Velázquez AI 6(5) 102 (2025) https://doi.org/10.3390/ai6050102
SMBH binary candidate PKS J2134−0153: possible multi-band periodic variability and inter-band time lags
Guo-Wei Ren, Mouyuan Sun, Nan Ding, Xing Yang and Zhi-Xiang Zhang Monthly Notices of the Royal Astronomical Society 537(3) 2931 (2025) https://doi.org/10.1093/mnras/stae2553
AstroM3: A Self-supervised Multimodal Model for Astronomy
Finding radio transients with anomaly detection and active learning based on volunteer classifications
Alex Andersson, Chris Lintott, Rob Fender, Michelle Lochner, Patrick Woudt, Jakob van den Eijnden, Alexander van der Horst, Assaf Horesh, Payaswini Saikia, Gregory R Sivakoff, Lilia Tremou and Mattia Vaccari Monthly Notices of the Royal Astronomical Society 538(3) 1397 (2025) https://doi.org/10.1093/mnras/staf336
Astronomaly at scale: searching for anomalies amongst 4 million galaxies
V Etsebeth, M Lochner, M Walmsley and M Grespan Monthly Notices of the Royal Astronomical Society 529(1) 732 (2024) https://doi.org/10.1093/mnras/stae496
Classification of Variable Star Light Curves with Convolutional Neural Network
An Automated Catalog of Long Period Variables using Infrared Lightcurves from Palomar Gattini-IR
Aswin Suresh, Viraj Karambelkar, Mansi M. Kasliwal, Michael C. B. Ashley, Kishalay De, Matthew J. Hankins, Anna M. Moore, Jamie Soon, Roberto Soria, Tony Travouillon and Kayton K. Truong Publications of the Astronomical Society of the Pacific 136(8) 084203 (2024) https://doi.org/10.1088/1538-3873/ad68a4
Characterizing B stars from Kepler/K2 Campaign 11
Alan W. Pereira, Eduardo Janot-Pacheco, Marcelo Emilio, Laerte Andrade, James D. Armstrong, Jéssica M. Eidam, M. Cristina Rabello-Soares and Bergerson V. H. V. da Silva Astronomy & Astrophysics 686 A20 (2024) https://doi.org/10.1051/0004-6361/202346439
Felipe Elorrieta, Lucas Osses, Matias Cáceres, Susana Eyheramendy and Wilfredo Palma 3 (2023) https://doi.org/10.1007/978-3-031-40209-8_1
An innovative tool for automating classification of stellar variability through nonlinear data analytics
Sparse Logistic Regression for RR Lyrae versus Binaries Classification
Piero Trevisan, Mario Pasquato, Gaia Carenini, Nicolas Mekhaël, Vittorio F. Braga, Giuseppe Bono and Mohamad Abbas The Astrophysical Journal 950(2) 103 (2023) https://doi.org/10.3847/1538-4357/accf8f
Automated classification of eclipsing binary systems in the VVV Survey
I V Daza-Perilla, L V Gramajo, M Lares, et al. Monthly Notices of the Royal Astronomical Society 520(1) 828 (2023) https://doi.org/10.1093/mnras/stad141
Finding Fast Transients in Real Time Using a Novel Light-curve Analysis Algorithm
Robert Strausbaugh, Antonino Cucchiara, Michael Dow Jr., Sara Webb, Jielai Zhang, Simon Goode and Jeff Cooke The Astronomical Journal 163(2) 95 (2022) https://doi.org/10.3847/1538-3881/ac441b
YOUNG Star detrending for Transiting Exoplanet Recovery (YOUNGSTER) – II. Using self-organizing maps to explore young star variability in sectors 1–13 of TESS data
Matthew P Battley, David J Armstrong and Don Pollacco Monthly Notices of the Royal Astronomical Society 511(3) 4285 (2022) https://doi.org/10.1093/mnras/stac278
Kepler Uzay Teleskobu ve ASAS Görüş Alanındaki Sefeid Türü Değişen Yıldızların Frekans Analizi
Semi-supervised classification and clustering analysis for variable stars
R Pantoja, M Catelan, K Pichara and P Protopapas Monthly Notices of the Royal Astronomical Society 517(3) 3660 (2022) https://doi.org/10.1093/mnras/stac2715
A novel bivariate autoregressive model for predicting and forecasting irregularly observed time series
Felipe Elorrieta, Susana Eyheramendy, Wilfredo Palma and Cesar Ojeda Monthly Notices of the Royal Astronomical Society 505(1) 1105 (2021) https://doi.org/10.1093/mnras/stab1216
Alert Classification for the ALeRCE Broker System: The Light Curve Classifier
P. Sánchez-Sáez, I. Reyes, C. Valenzuela, F. Förster, S. Eyheramendy, F. Elorrieta, F. E. Bauer, G. Cabrera-Vives, P. A. Estévez, M. Catelan, G. Pignata, P. Huijse, D. De Cicco, P. Arévalo, R. Carrasco-Davis, J. Abril, R. Kurtev, J. Borissova, J. Arredondo, E. Castillo-Navarrete, D. Rodriguez, D. Ruz-Mieres, A. Moya, L. Sabatini-Gacitúa, C. Sepúlveda-Cobo and E. Camacho-Iñiguez The Astronomical Journal 161(3) 141 (2021) https://doi.org/10.3847/1538-3881/abd5c1
Classification of Variable Stars Light Curves Using Long Short Term Memory Network
New insights into time-series analysis IV: panchromatic and flux-independent period finding methods
C E Ferreira Lopes, N J G Cross and F Jablonski Monthly Notices of the Royal Astronomical Society 501(3) 4123 (2021) https://doi.org/10.1093/mnras/staa3967
A method for finding anomalous astronomical light curves and their analogues
J Rafael Martínez-Galarza, Federica B Bianco, Dennis Crake, et al. Monthly Notices of the Royal Astronomical Society 508(4) 5734 (2021) https://doi.org/10.1093/mnras/stab2588
Variability, periodicity, and contact binaries in WISE
Evan Petrosky, Hsiang-Chih Hwang, Nadia L Zakamska, Vedant Chandra and Matthew J Hill Monthly Notices of the Royal Astronomical Society 503(3) 3975 (2021) https://doi.org/10.1093/mnras/stab592
Informative Bayesian model selection for RR Lyrae star classifiers
F Pérez-Galarce, K Pichara, P Huijse, M Catelan and D Mery Monthly Notices of the Royal Astronomical Society 503(1) 484 (2021) https://doi.org/10.1093/mnras/stab320
The Automatic Learning for the Rapid Classification of Events (ALeRCE) Alert Broker
F. Förster, G. Cabrera-Vives, E. Castillo-Navarrete, P. A. Estévez, P. Sánchez-Sáez, J. Arredondo, F. E. Bauer, R. Carrasco-Davis, M. Catelan, F. Elorrieta, S. Eyheramendy, P. Huijse, G. Pignata, E. Reyes, I. Reyes, D. Rodríguez-Mancini, D. Ruz-Mieres, C. Valenzuela, I. Álvarez-Maldonado, N. Astorga, J. Borissova, A. Clocchiatti, D. De Cicco, C. Donoso-Oliva, L. Hernández-García, et al. The Astronomical Journal 161(5) 242 (2021) https://doi.org/10.3847/1538-3881/abe9bc
TESS Data for Asteroseismology (T’DA) Stellar Variability Classification Pipeline: Setup and Application to the Kepler Q9 Data
J. Audenaert, J. S. Kuszlewicz, R. Handberg, A. Tkachenko, D. J. Armstrong, M. Hon, R. Kgoadi, M. N. Lund, K. J. Bell, L. Bugnet, D. M. Bowman, C. Johnston, R. A. García, D. Stello, L. Molnár, E. Plachy, D. Buzasi and C. Aerts The Astronomical Journal 162(5) 209 (2021) https://doi.org/10.3847/1538-3881/ac166a
Identifying Periodic Variable Stars and Eclipsing Binary Systems with Long-term Las Cumbres Observatory Photometric Monitoring of ZTF J0139+5245
Zwicky Transient Facility and Globular Clusters: the Period–Luminosity and Period–Luminosity–Color Relations for Late-type Contact Binaries
Chow-Choong Ngeow, Szu-Han Liao, Eric C. Bellm, Dmitry A. Duev, Matthew J. Graham, Ashish A. Mahabal, Frank J. Masci, Michael S. Medford, Reed Riddle and Ben Rusholme The Astronomical Journal 162(2) 63 (2021) https://doi.org/10.3847/1538-3881/ac01ea
A Comprehensive Comparison of Period Extraction Algorithms for Asteroids with Long Term Observation
The ZTF Source Classification Project. I. Methods and Infrastructure
Jan van Roestel, Dmitry A. Duev, Ashish A. Mahabal, Michael W. Coughlin, Przemek Mróz, Kevin Burdge, Andrew Drake, Matthew J. Graham, Lynne Hillenbrand, Eric C. Bellm, Thomas Kupfer, Alexandre Delacroix, C. Fremling, V. Zach Golkhou, David Hale, Russ R. Laher, Frank J. Masci, Reed Riddle, Philippe Rosnet, Ben Rusholme, Roger Smith, Maayane T. Soumagnac, Richard Walters, Thomas A. Prince and S. R. Kulkarni The Astronomical Journal 161(6) 267 (2021) https://doi.org/10.3847/1538-3881/abe853
Probing the interior physics of stars through asteroseismology
A survey on machine learning based light curve analysis for variable astronomical sources
Ce Yu, Kun Li, Yanxia Zhang, Jian Xiao, Chenzhou Cui, Yihan Tao, Shanjiang Tang, Chao Sun and Chongke Bi WIREs Data Mining and Knowledge Discovery 11(5) (2021) https://doi.org/10.1002/widm.1425
The VISTA Variables in the Vía Láctea infrared variability catalogue (VIVA-I)
Christopher M P Russell, J R De Medeiros, C Cortés, et al. Monthly Notices of the Royal Astronomical Society 496(2) 1730 (2020) https://doi.org/10.1093/mnras/staa1352
Recovering variable stars in large surveys: EAup Algol-type class in the Catalina Survey
A Carmo, C E Ferreira Lopes, A Papageorgiou, et al. Monthly Notices of the Royal Astronomical Society 498(2) 2833 (2020) https://doi.org/10.1093/mnras/staa2518
Near-infrared Search for Fundamental-mode RR Lyrae Stars toward the Inner Bulge by Deep Learning
Unsupervised machine learning for transient discovery in deeper, wider, faster light curves
Sara Webb, Michelle Lochner, Daniel Muthukrishna, et al. Monthly Notices of the Royal Astronomical Society 498(3) 3077 (2020) https://doi.org/10.1093/mnras/staa2395
An Information Theory Approach on Deciding Spectroscopic Follow-ups
An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves
Christian Pieringer, Karim Pichara, Márcio Catelán and Pavlos Protopapas Monthly Notices of the Royal Astronomical Society 484(3) 3071 (2019) https://doi.org/10.1093/mnras/stz106
Into the Darkness: Classical and Type II Cepheids in the Zona Galactica Incognita
Classifying Periodic Astrophysical Phenomena from non-survey optimized variable-cadence observational data
Paul R. McWhirter, Abir Hussain, Dhiya Al-Jumeily, Iain A. Steele and Marley M.B.R. Vellasco Expert Systems with Applications 131 94 (2019) https://doi.org/10.1016/j.eswa.2019.04.035
Discrete-time autoregressive model for unequally spaced time-series observations
Variability search in M 31 using principal component analysis and the Hubble Source Catalogue
M I Moretti, D Hatzidimitriou, A Karampelas, et al. Monthly Notices of the Royal Astronomical Society 477(2) 2664 (2018) https://doi.org/10.1093/mnras/sty758
New variable stars from the photographic archive: semi-automated discoveries, attempts at automatic classification and the new field 104 Her
New Insights into Time Series Analysis III: Setting constraints on period analysis
C E Ferreira Lopes, N J G Cross and F Jablonski Monthly Notices of the Royal Astronomical Society 481(3) 3083 (2018) https://doi.org/10.1093/mnras/sty2469
Machine-learning-based Brokers for Real-time Classification of the LSST Alert Stream
Gautham Narayan, Tayeb Zaidi, Monika D. Soraisam, Zhe Wang, Michelle Lochner, Thomas Matheson, Abhijit Saha, Shuo Yang, Zhenge Zhao, John Kececioglu, Carlos Scheidegger, Richard T. Snodgrass, Tim Axelrod, Tim Jenness, Robert S. Maier, Stephen T. Ridgway, Robert L. Seaman, Eric Michael Evans, Navdeep Singh, Clark Taylor, Jackson Toeniskoetter, Eric Welch and Songzhe Zhu The Astrophysical Journal Supplement Series 236(1) 9 (2018) https://doi.org/10.3847/1538-4365/aab781
GRAPE: Genetic Routine for Astronomical Period Estimation
Paul R McWhirter, Iain A Steele, Abir Hussain, Dhiya Al-Jumeily and Marley M B R Vellasco Monthly Notices of the Royal Astronomical Society 479(4) 5196 (2018) https://doi.org/10.1093/mnras/sty1823
An irregular discrete time series model to identify residuals with autocorrelation in astronomical light curves
Susana Eyheramendy, Felipe Elorrieta and Wilfredo Palma Monthly Notices of the Royal Astronomical Society 481(4) 4311 (2018) https://doi.org/10.1093/mnras/sty2487
Comparative performance of selected variability detection techniques in photometric time series data
K. V. Sokolovsky, P. Gavras, A. Karampelas, et al. Monthly Notices of the Royal Astronomical Society 464(1) 274 (2017) https://doi.org/10.1093/mnras/stw2262
Multiwavelength variability study and search for periodicity of PKS 1510–089
Variable classification in the LSST era: exploring a model for quasi-periodic light curves
J. C. Zinn, C. S. Kochanek, S. Kozłowski, et al. Monthly Notices of the Royal Astronomical Society 468(2) 2189 (2017) https://doi.org/10.1093/mnras/stx586
Machine learning techniques to select Be star candidates
An autoregressive model for irregular time series of variable stars
Susana Eyheramendy, Felipe Elorrieta and Wilfredo Palma Proceedings of the International Astronomical Union 12(S325) 259 (2016) https://doi.org/10.1017/S1743921317000448
An analysis of feature relevance in the classification of astronomical transients with machine learning methods
A. D'Isanto, S. Cavuoti, M. Brescia, et al. Monthly Notices of the Royal Astronomical Society 457(3) 3119 (2016) https://doi.org/10.1093/mnras/stw157
Skysurveys, Light Curves and Statistical Challenges
Paul R. McWhirter, Sean Wright, Iain A. Steele, et al. Lecture Notes in Computer Science, Intelligent Computing Theories and Application 9771 820 (2016) https://doi.org/10.1007/978-3-319-42291-6_81
A machine learned classifier for RR Lyrae in the VVV survey
S. D. Kügler, N. Gianniotis and K. L. Polsterer Monthly Notices of the Royal Astronomical Society 451(4) 3385 (2015) https://doi.org/10.1093/mnras/stv1181
A NEW CATALOG OF VARIABLE STARS IN THE FIELD OF THE OPEN CLUSTER M37
Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases
Pablo Huijse, Pablo A. Estevez, Pavlos Protopapas, Jose C. Principe and Pablo Zegers IEEE Computational Intelligence Magazine 9(3) 27 (2014) https://doi.org/10.1109/MCI.2014.2326100
Comparative Analysis of a Transition Region Bright Point with a Blinker and Coronal Bright Point Using Multiple EIS Emission Lines
Exhausting the information: novel Bayesian combination of photometric redshift PDFs
Matias Carrasco Kind and Robert J. Brunner Monthly Notices of the Royal Astronomical Society 442(4) 3380 (2014) https://doi.org/10.1093/mnras/stu1098
A mid-infrared study of RR Lyrae stars with the Wide-field Infrared Survey Explorer all-sky data release
Tatyana Gavrilchenko, Christopher R. Klein, Joshua S. Bloom and Joseph W. Richards Monthly Notices of the Royal Astronomical Society 441(1) 715 (2014) https://doi.org/10.1093/mnras/stu606
The VVV Templates Project Towards an automated classification of VVV light-curves