Fengchun Peng, Robert A. Jacobs, Martin A. Tanner, Bayesian Inference in Mixtures-of-Experts and Hierarchical Mixtures-of-Experts Models With an Application to Speech Recognition, Journal of the ...

Bayesian statistics represents a powerful framework for data analysis that centres on Bayes’ theorem, enabling researchers to update existing beliefs with incoming evidence. By combining prior ...

Causal effects are comparisons among values that would have been observed under all possible assignments of treatments to experimental units. In an experiment, one assignment of treatments is chosen ...

Generative AI Beyond the Black Box: A Bayesian Model for LLM Reasoning, Inference and Applications Abstract Generative AI, based on Large Language Models (LLMs), has become very popular. In this talk, ...

Explore Bayesian Networks, their principles, applications, and impact on AI and probabilistic reasoning with AI Terminologies 101.

Statistical decision theory: risk, decision rules, loss and utility functions, Bayesian expected loss, Frequentist risk. Bayesian Inference: Bayes theorem, prior, posterior and predictive ...