ASTRAFier is a Transformer-BiLSTM-CNN model that classifies stellar variability from light curves, reporting 94.26% accuracy on Kepler data and 88.22% on TESS, then applied to 2.8 million TESS curves to release a catalog.
2018a, MNRAS
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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UNVERDICTED 2representative citing papers
In a bias-cleaned sample of main-sequence stars, magnetic activity above solar maximum accounts for non-detection of p-modes in 32% of cases where amplitude is predicted sufficient, while stars with photometric activity index above 2000 ppm have 98.3% probability of no detected oscillations.
citing papers explorer
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ASTRAFier: A Novel and Scalable Transformer-based Stellar Variability Classifier
ASTRAFier is a Transformer-BiLSTM-CNN model that classifies stellar variability from light curves, reporting 94.26% accuracy on Kepler data and 88.22% on TESS, then applied to 2.8 million TESS curves to release a catalog.
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Revisiting the impact of stellar magnetic activity on the detectability of solar-like oscillations by Kepler
In a bias-cleaned sample of main-sequence stars, magnetic activity above solar maximum accounts for non-detection of p-modes in 32% of cases where amplitude is predicted sufficient, while stars with photometric activity index above 2000 ppm have 98.3% probability of no detected oscillations.