If referencing content from this tutorial, please reference the book Enhancing Deep Learning with Bayesian Inference by Matt Benatan, Jochem Gietema, and Marian Schneider. Bibtex reference: ...

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 ...

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

ABSTRACT: This paper presents an effective Bayesian network model for medical diagnosis. The proposed approach consists of two stages. In the first stage, a novel feature selection algorithm with ...

ABSTRACT: The entrepreneurial attitude model is nowadays getting more attention as a framework to explain and describe new business creation. In short, the attitude model posits that the ...

Over the past 2 decades Bayesian methods have been gaining popularity in many scientific disciplines. However, to this date, they are rarely part of formal graduate statistical training in clinical ...

This narrative review intends to provide the anesthesiologist with the basic knowledge of the Bayesian concepts and should be considered as a tutorial for anesthesiologists in the concept of Bayesian ...