Gaussian Process Regression for Astronomical Time Series
The past two decades have seen a major expansion in the availability, size, and precision of time-domain data sets in astronomy. Owing to their unique combination of flexibility, mathematical simplicity, and comparative robustness, Gaussian processes (GPs) have emerged recently as the solution of ch...
Main Authors: | Aigrain, S, Foreman-Mackey, D |
---|---|
Format: | Journal article |
Language: | English |
Published: |
Annual Reviews
2023
|
Similar Items
-
Inferring probabilistic stellar rotation periods using Gaussian processes
by: Angus, R, et al.
Published: (2017) -
Gaussian processes for time-series modelling.
by: Roberts, S, et al.
Published: (2013) -
Sparse Gaussian Process Regression for Landslide Displacement Time-Series Forecasting
by: Weiqi Yang, et al.
Published: (2022-06-01) -
PYANETI II: a multi-dimensional Gaussian process approach to analysing spectroscopic time-series
by: Barragán, O, et al.
Published: (2021) -
Gaussian process regression as a powerful tool for analysing time series in environmental geochemistry
by: Teba Gil-Díaz, et al.
Published: (2024-12-01)