Revision 3f74b5c7f08271d3ee7ba4610cc5d832bf0c5af0 authored by Fergus on 08 April 2022, 14:35:58 UTC, committed by GitHub on 08 April 2022, 14:35:58 UTC
* Remove positive transform for anisotropic lengthscales in higher dims * Add cosine to ard tests
1 parent 41fc73c
GLOSSARY.md
## Glossary
GPflow does not always follow standard Python naming conventions,
and instead tries to apply the notation in the relevant GP papers.\
The following is the convention we aim to use in the code.
---
<dl>
<dt>GPR</dt>
<dd>Gaussian process regression</dd>
<dt>SVGP</dt>
<dd>stochastic variational inference for Gaussian process models</dd>
<dt>Shape constructions [..., A, B]</dt>
<dd>the way of describing tensor shapes in docstrings and comments. Example: <i>[..., N, D, D]</i>, this is a tensor with an arbitrary number of leading dimensions indicated using the ellipsis sign, and the last two dimensions are equal</dd>
<dt>X</dt>
<dd>(and variations like Xnew) refers to input points; always of rank 2, e.g. shape <i>[N, D]</i>, even when <i>D=1</i></dd>
<dt>Y</dt>
<dd>(and variations like Ynew) refers to observed output values, potentially with multiple output dimensions; always of rank 2, e.g. shape <i>[N, P]</i>, even when <i>P=1</i></dd>
<dt>Z</dt>
<dd>refers to inducing points</dd>
<dt>M</dt>
<dd>stands for the number of inducing features (e.g. length of Z)</dd>
<dt>N</dt>
<dd>stands for the number of data or minibatch size in docstrings and shape constructions</dd>
<dt>P</dt>
<dd>stands for the number of output dimensions in docstrings and shape constructions</dd>
<dt>D</dt>
<dd>stands for the number of input dimensions in docstrings and shape constructions</dd>
</dl>
![swh spinner](/static/img/swh-spinner.gif)
Computing file changes ...