https://github.com/GPflow/GPflow
Revision 235853956f699c32dcc9ce4c4311724c3f90705a authored by st-- on 15 April 2020, 12:19:00 UTC, committed by GitHub on 15 April 2020, 12:19:00 UTC
Release notes:
- Improve structure of likelihoods subdirectory (#1416)
- Update README.md (#1401) and GPflow 2 upgrade guide (#1414)
- Improved handling of invalid values for constrained Parameters (#1408)
- Improvements on types/function annotations (#1406, #1420)
- Documentation improvements (metalearning with GPs: #1382, coregionalization notebook: #1402, MCMC notebook: #1410, intro to gpflow with tensorflow 2: #1413)
- Minor documentation fixes (#1429, #1430, #1433)
- Fix: move matplotlib import inside ImageToTensorBoard (#1399)
- Fix: tf.function compilation of ndiagquad (#1418)
- Fix: cache tensorboard file writers and re-use them (#1424)
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Tip revision: 235853956f699c32dcc9ce4c4311724c3f90705a authored by st-- on 15 April 2020, 12:19:00 UTC
Release 2.0.1 (#1436)
Tip revision: 2358539
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>
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