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ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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Benchmark datasets used in "Classification of Periodic Variables with Cyclic-Permutation Invariant Neural Networks"

Authors: Keming Zhang; Joshua Bloom;

Benchmark datasets used in "Classification of Periodic Variables with Cyclic-Permutation Invariant Neural Networks"

Abstract

To aid the reproducibility of the results in the paper “Classification of Periodic Variables with Cyclic-Permutation Invariant Neural Networks,” we make our aggregation of the following data available. Code used to load the data and generate the results can be found at https://github.com/kmzzhang/periodicnetwork. These datasets have been constructed from publicly available data sources. If you use these datasets, please cite the original papers [1, 2, 3], in addition to ours [TBD]. Others might find this data useful for testing time-series inference techniques. [1] Jayasinghe, T. et al. The ASAS-SN catalogue of variable stars I: The Serendipitous Survey. Monthly Notices of the Royal Astronomical Society 477, 3145–3163 (2018). URL https://academic.oup.com/mnras/article/477/3/3145/4961151. [2] Alcock, C. et al. The MACHO Project LMC Variable Star Inventory.II.LMC RR Lyrae Stars- Pulsational Characteristics and Indications of a Global Youth of the LMC. The Astronomical Journal 111, 1146 (1996). URL http://adsabs.harvard.edu/abs/1996AJ....111.1146A. [3] Udalski, A. The Optical Gravitational Lensing Experiment. Real Time Data Analysis Systems in the OGLE-III Survey. Acta Astronomica 53, 291–305 (2003). URL http: //adsabs.harvard.edu/abs/2003AcA....53..291U.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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