Gaussian processes with PyTorch
$ pip install gptorch
You can now do:
$ pip install -r -requirements.txt
$ python setup.py install
Otherwise, we've provided an environment.yml to make a new virtual environment with Anaconda:
$ conda env create -f environment.yml
$ source activate gptorch
- Vanilla GP regression model
- Sparse GP (variational free energy model)
- Sparse Variational GP
- FITC sparse GPs
- Structured ("Kronecker") GPs
- Bayesian GPLVM
- Dynamical GP-LVM/Bayesian warped GP
- Non-Gaussian likelihoods (e.g. for classification)
- Correlated outputs
- Deep GPs