Abstract: The rapid expansion of large language models (LLMs) has led to increasingly frequent interactions between LLM agents and human users, motivating new questions about their capacity to form ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

In A Nutshell Alpha brain waves cycling at 8-13 times per second determine how wide your “temporal binding window,” or the ...

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

This article explores the potential of large language models (LLMs) in reliability systems engineering, highlighting their applications in improving industrial efficiency and flexibility. It also ...

This paper presents a valuable software package, named "Virtual Brain Inference" (VBI), that enables faster and more efficient inference of parameters in dynamical system models of whole-brain ...

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 ...

Version of Record: This is the final version of the article. This work proposes a new approach to analyse cell-count data from multiple brain regions. Collecting such data can be expensive and ...

This research evaluates the effect of monetary policy rate and exchange rate on inflation across continents using both Frequentist and Bayesian Generalized Additive Mixed Models (GAMMs). Extending an ...

Abstract: In this paper, a new extension of the Rayleigh-Weibull (RW) model, called the sine Rayleigh-Weibull (SRW) model, is proposed. This model is constructed using the trigonometrically generated ...