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/1D_toy_data
- Simple_test.csv
- Simple_train.csv
Get the dataset here. The folders should look like this:
data/taxi-data
- test.csv
- train.csv
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
[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