Outline In this tutorial I am going to present the use of SpeciesNetwork (Zhang et al. 2017), which is implemented as an add-on package for BEAST2 (Bouckaert et al. 2019) and allows the joint Bayesian ...
In this tutorial, we explore hierarchical Bayesian regression with NumPyro and walk through the entire workflow in a structured manner. We start by generating synthetic data, then we define a ...
PAC-Bayesian theory provides three generalization bounds: Occam bound for finite precision parameters, PAC-Bayesian bound for posterior distributions including dropout training, and training-variance ...
Abstract: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the third volume of ten from the Conference ...
In this tutorial, we implement an advanced Bayesian hyperparameter optimization workflow using Hyperopt and the Tree-structured Parzen Estimator (TPE) algorithm. We construct a conditional search ...
This book's organization : read me first! -- Introduction : models we believe in -- What is this stuff called probability? -- Bayes' rule -- Inferring a binomial proportion via exact mathematical ...
ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...