Exposure-integrated Gaussian processes allow prediction of both latent stellar signals and instrument-specific binned versions, supporting combination of overlapping EPRV datasets with varying exposure times.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
A time-aware convolutional attention network trained on StarSim synthetic spectra reduces stellar activity radial velocity jitter to 52.5% and 62.4% of original levels in HARPS and CARMENES data for epsilon Eridani and TZ Arietis.
citing papers explorer
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Exposure-averaged Gaussian Processes for Combining Overlapping Datasets
Exposure-integrated Gaussian processes allow prediction of both latent stellar signals and instrument-specific binned versions, supporting combination of overlapping EPRV datasets with varying exposure times.
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Mitigating stellar radial velocity jitter using orthogonal activity indices and a time-aware neural network
A time-aware convolutional attention network trained on StarSim synthetic spectra reduces stellar activity radial velocity jitter to 52.5% and 62.4% of original levels in HARPS and CARMENES data for epsilon Eridani and TZ Arietis.