Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet parameter inference for such models remains highly challenging—particularly when ...

ABSTRACT: Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet parameter inference for such models remains highly ...

Normalizing constant (also called partition function, Bayesian evidence, or marginal likelihood) is one of the central goals of Bayesian inference, yet most of the existing methods are both expensive ...

Abstract: Normalizing constant recurrence equations play an important role in the exact analysis of load-independent (LI) product-form queueing networks. However, they have not been extended to the ...