The focus of this tutorial is to introduce uncertainty propagation from the data to the inferred parameters. The tutorials are presented using the Jupyter Notebooks. Several ways to run the Jupyter ...

A short step by step exercise to write a Bayesian Model using a MCMC algorithm in R & C++. In Bayesian analysis, a prior is used in conjunction with Bayes' theorem to update the probability of an ...

Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain Monte-Carlo ...