Reduced Bayesian Neural Networks are Deterministic Neural Networks with a Bayesian subset of weights. redBNN class computes a MAP estimate of the entire NN and then performs Bayesian inference on a chosen layer (--reduction=layers) or block (--reduction=blocks).
This library is built upon pyro and torchvision: redbnn loads any pre-trained architecture from torchvision library and trains a deterministic Neural Network (baseNN) or a reduced Bayesian Neural Network (redBNN) using Stochastic Variational Inference (SVI) or Hamiltonian Monte Carlo (HMC) from pyro library.
An example of training with baseNN or redBNN is provided by the script training.py.
Install: pip install redbnn
Documentation: https://redbnn.readthedocs.io/en/latest/