To address the limitations of binary pCR classification, Pusztai and colleagues developed the residual cancer burden (RCB) ...

SEED-SET enhances ethical evaluation of autonomous systems through a hierarchical Bayesian framework, optimizing alignment ...

(spidroins) through long-read transcriptomics across a broad phylogenetic range, with theoretical implications for protein family evolution, biomaterials, and silk biology. By identifying putative ...

People often solve simple arithmetic problems, such as basic addition, subtraction, multiplication or division, in their ...

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

Nguyen Xuan Long, a globally recognized expert in statistical inference and machine learning currently based in the United ...

Scientists have quantified what draws mosquitoes to people—which could help make better, life-saving bug traps.

The course is structured in four main parts, covering the full Bayesian workflow: from probabilistic reasoning to advanced modeling. BAYESIANLEARNING/ │ ├── PART-I/ │ ├── theory/ │ │ └── ...

Abstract: Sparse diagnosis techniques for antenna arrays provide an efficient approach to fault diagnosis by leveraging the sparse nature of faulty elements. In practical scenarios, an unknown ...

This repository includes theoretical notes, slides, and hands-on R examples for exploring Bayesian Linear Regression. It introduces both classical and Bayesian regression methods, showing how to ...

The European Medicines Agency (EMA) has begun a consultation into the use of Bayesian methods in the analysis of clinical trial data. Bayesian methods are one of the main approaches to statistical ...