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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