The collection of GP visualizations. The GP computation part benefits from TensorFlow 2.0 and GPflow 2.0, whereas the visualization implemetation sits on top of the holoviews framework, which in turn based on bokeh.
Any contributions or ideas about visualizations which you think could be helpful are welcome.
- GP samples for squared exponential, matern52, matern32, matern12, arccosine 0th order and linear kernels
- GPR model visualization with different kernels and ability to add new data points
- SVGP online training, moving inducing points
Using conda is optional, but still it is recommended in the case when you don't want to collide with existing packages like TensorFlow or GPflow
conda activate your-env
(your-env) pip install -r requirements.txt
(your-env) pip install -e .
(your-env) bokeh serve --show apps/samples.py
You can run the same plots in a notebook - check notebooks
folder.