Abstract
This submission includes a simplified version of some code we have been developing for fast training of Gaussian processes. We also include a sample data set, which is NOAA tidal data from Woods Hole in the US, downloaded from http://tidesandcurrents.noaa.gov/ .
The code and data included here were used to produce the numerical results in the following paper:
[1] Fast methods for training Gaussian processes, C. J. Moore, A. J. K. Chua, C. P. L. Berry, and J. R. Gair (2016), submitted to RSOS.
The code and data included here were used to produce the numerical results in the following paper:
[1] Fast methods for training Gaussian processes, C. J. Moore, A. J. K. Chua, C. P. L. Berry, and J. R. Gair (2016), submitted to RSOS.
Data Citation
Moore, Christopher J; Chua, Alvin J K; Berry, Christopher P L; Gair, Jonathan R. (2016). Fast methods for training Gaussian processes, [software]. http://dx.doi.org/10.7488/ds/1343.
| Date made available | 29 Feb 2012 |
|---|---|
| Publisher | Edinburgh DataShare |