VIND
Variational Inference using Numerical Differentiation for Non-Reparameterisable Parameters
Dependencies
Python 3.6 with following packages
numpy, scipy, scikit-learn, pytorch, matplotlib, sacred, pandas, tqdm
For reproducing experiments, please run the following files using python {filename} and
subsequently plot the used figures with python create_plots.py.
- linear_regression.py
- mse_grad_gamma.py
- wishart_student_normal.py
- wishart_normal_normal.py
For the stationarity test on the included data, use R to run stationarity.R.
Data
Used standard ML benchmark data sets as well as openly accessible historical data from yahoo finance. For more information on the individual files used, see here.