IEEE

Adaptive Decision-Making in Attack-Defense Games With Bayesian Inference of Rationality Level

Abstract: This article investigates two-player attack-defense (AD) games involving players with bounded rationality, where the defender aims to intercept the attacker, while the attacker aims to ...
College of Computing - Georgia Tech

Guess Who: New Framework Advances Probabilistic Capabilities in LLMs

That’s because a new framework is improving the probabilistic reasoning of LLMS like ChatGPT and Gemini. School of ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
IEEE

Bayesian Neural Networks via MCMC: A Python-Based Tutorial

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