Abstract: Sparse Bayesian learning (SBL) is an advanced statistical framework that dominantly enhances the sparse features of targets of interest in radar imagery. A widely adopted strategy for ...
Modeling Person Guessing as a Random Effect: A Bayesian Approach of the Two-Parameter Logistic Model
The final, formatted version of the article will be published soon. Guessing behavior has been an enduring problem that undermines the validity and interpretability of scores from MC items. The ...
These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.
Abstract: This paper proposes a variational Bayesian inference (VBI) based algorithm for gridless and online estimation of multiple two-dimensional directions of arrival (2D-DOAs), whose number and ...
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 ...
In this work, we develop a new framework for designing experiments that are robust to model misspecification through generalised Bayesian inference. This repository contains the files needed to ...
For the past decade, the spotlight in artificial intelligence has been monopolized by training. The breakthroughs have largely come from massive compute clusters, trillion-parameter models, and the ...
ABSTRACT: Special education services are designed to provide tailored support for students with diverse learning needs, with the expectation of improving academic achievement. This study examines the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results