A better uncertainty estimate for deep neural networks using pruning methods
Implementation of weights based and filter based pruning methods and their effect on the uncertainty estimate for deep neural networks. Uncertainty estimate is computed using entropy on the empirical pdm of outputs using Monte Carlo Dropout technique.