Category: optimizationPage 3 of 3

Huggins20_Validated Variational Inference via Practical Posterior Error Bounds

Three criteria are reviewed. KL divergence -divergence Wasserstein distance bound the difference between expectation of any smooth function. With upper bounds on the function of interest and the…

Approximate Bayesian Inference

Computing the posterior is our target. Expectation to get the marginal as we might not know the exact data distribution. Even if we do, computation is burdensome in…

Maintenance models

There are three types of maintenance model: reactive, preventive, predictive. It is important to realize the difference between the action of inspection and maintenance. Inspection lead to preventive…

automatic differentiation

Use cases: map, mle estimators with gradient descent or quasi Newton methods (1) posterior sampling with HMC (log density, 1 for Euclidean, 3 for Riemannian) standard error, posterior…