no code implementations • 22 Sep 2022 • Killian Wood, Alec M. Dunton, Amanda Muyskens, Benjamin W. Priest
Gaussian processes (GPs) are Bayesian non-parametric models popular in a variety of applications due to their accuracy and native uncertainty quantification (UQ).
1 code implementation • 31 Aug 2022 • Imène R. Goumiri, Alec M. Dunton, Amanda L. Muyskens, Benjamin W. Priest, Robert E. Armstrong
In particular, a single light curve can feature hundreds of thousands of observations, which is well beyond the practical realization limits of a conventional GP on a single machine.
no code implementations • 22 May 2022 • Alec M. Dunton, Benjamin W. Priest, Amanda Muyskens
Gaussian processes (GPs) are Bayesian non-parametric models useful in a myriad of applications.