Training algorithms, broadly construed, are an essential part of every d...
The linearized-Laplace approximation (LLA) has been shown to be effectiv...
Neural operators are a type of deep architecture that learns to solve (i...
Monte Carlo (MC) integration is the de facto method for approximating th...
Deep neural networks are prone to overconfident predictions on outliers....
Bayesian formulations of deep learning have been shown to have compellin...
Continually learning new skills is important for intelligent systems, ye...
Bayesian methods promise to fix many shortcomings of deep learning, but ...