Bayesian Deep Learning
Quantify uncertainty in deep learning.
Bayesian Neural Networks
Weight distributions. Variational inference.
Monte Carlo Dropout
Dropout at inference. Ensemble of drops.
Deep Ensembles
Multiple models. Combine predictions.
Key Takeaways
- BNNs with weight uncertainty
- MC dropout
- Deep ensembles