to model uncertainty in the prediction (Blundell et al., 2015) 1. regularisation via a compression cost on the weights 2. richer representations and predictions from cheap model averaging, and 3. exploration in simple reinforcement learning problems such as contextual bandits. • Another way to avoid over-fitting (e.g., early stopping, weight decay, dropout, etc.) 8 • Basic Concepts • Active Learning? • Bayesian Neural Networks? • Siddhant & Lipton, 2018 • Learning Resources