Introduces MGIC_rv, an information criterion that combines conditional RV likelihood with an effective parameter count for selecting multi-GP models focused on radial velocities.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Deep neural networks using temperature-based spectral representations recover planetary Doppler signals with amplitudes of at least 25 cm/s from HARPS-N solar spectra under cross-validation.
The transmission spectrum of AU Mic b is dominated by the transit light source effect from stellar spots, yielding only weak atmospheric constraints with a preferred scale height below 185 km.
citing papers explorer
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A Model Selection Criterion for Multidimensional Gaussian Processes: Application to Radial Velocities
Introduces MGIC_rv, an information criterion that combines conditional RV likelihood with an effective parameter count for selecting multi-GP models focused on radial velocities.
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Modeling Doppler Shifts in Radial-Velocity Data with Deep Learning toward Earth-mass Exoplanet Detection
Deep neural networks using temperature-based spectral representations recover planetary Doppler signals with amplitudes of at least 25 cm/s from HARPS-N solar spectra under cross-validation.
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The HST/WFC3 Transmission Spectrum of AU Mic b Part I: An Atmosphere Obscured by Contamination and Systematics
The transmission spectrum of AU Mic b is dominated by the transit light source effect from stellar spots, yielding only weak atmospheric constraints with a preferred scale height below 185 km.