Neural Inference of Gaussian Processes for Time Series Data of Quasars. (arXiv:2211.10305v1 [astro-ph.GA])

The study of quasar light curves poses two problems: inference of the power
spectrum and interpolation of an irregularly sampled time series. A baseline
approach to these tasks is to interpolate a time series with a Damped Random
Walk (DRW) model, in which the spectrum is inferred using Maximum Likelihood
Estimation (MLE). However, the DRW model does not describe the smoothness of
the time series, and MLE faces many problems in terms of optimization and
numerical precision. In this work, …

arxiv astro data gaussian processes inference processes series time series