Bayesian Machine Learning

This code is for the project for the master MVA course Bayesian Machine Learning, about variational approaches for Gaussian Process learning and inference [1].

Data layout

Toy data

data/1D_toy_data
    - Simple_test.csv
    - Simple_train.csv

New York Taxi

Get the dataset here. The folders should look like this:

data/taxi-data
    - test.csv
    - train.csv

Experiments

We provide notebooks to run experiments:

• Hand-coded GP regression using Numpy/Scipy
• A comparison of approximate GP regression schemes
• GP regression on the (massive) NYC Taxi dataset

References

[1] Titsias, M.. (2009). Variational Learning of Inducing Variables in Sparse Gaussian Processes. Proceedings of the Twelth International Conference on Artificial Intelligence and Statistics, in PMLR 5:567-574