Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments
This repo contains code to estimate uncertainty in deep learning models. It has basic implementations for:
Article: Overview of estimating uncertainty in deep neural networks
model.compile(opitimizer=optim, loss=gaussian_nll)
=>
model.compile(optimizer=optim, loss=gaussian_nll)
Hello! I am using your code to create a neural network. When it works it works wonderfully, but about 50% of the time it goes nuts and gives me outrageous values. Has this happened to you? It appears as if every other time I run it, the index of si and mu changes and so the results become erratic.
Also I would like to thank you for developing this code!
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