bayesian-deep-learning

## What I do - Build Bayesian neural networks - Quantify uncertainty in DL - Apply variational inference - Use Monte Carlo dropout ## When to use me When working on uncertainty quantification in deep learning. ## Key Concepts - Bayesian NNs - Variational inference - Dropout as Bayesian - Weight uncertainty - Epistemic uncertainty - Aleatoric uncertainty - Model calibration