Bayesian Neural Networks for Quantifying Uncertainty in Time-series Forecasts

Implementation of:

• David Mackay's Cheap and Cheerful approach to error prediction in Neural networks
• Monte Carlo Dropout as an approximation to Bayesian Neural Networks

Requires:

scipy
numpy
tensorflow-gpu=1.0
scikit-learn
seaborn
matplotlib
joblib