A new chi-square morphology method plus CNN classifies Kepler eclipsing binaries at 90% accuracy and flags four new temporally varying systems linked to magnetic activity.
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2 Pith papers cite this work. Polarity classification is still indexing.
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astro-ph.SR 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
SINet outperforms five prior statistical and deep learning methods on F10.7 predictions and provides the first deep learning forecasts for the F30 solar index.
citing papers explorer
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A New Methodology for Classifying Eclipsing Binaries with Kepler Data and Deep Learning
A new chi-square morphology method plus CNN classifies Kepler eclipsing binaries at 90% accuracy and flags four new temporally varying systems linked to magnetic activity.
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Daily Predictions of F10.7 and F30 Solar Indices with Deep Learning
SINet outperforms five prior statistical and deep learning methods on F10.7 predictions and provides the first deep learning forecasts for the F30 solar index.