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 ...
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 ...
Cybersecurity researchers have uncovered critical remote code execution vulnerabilities impacting major artificial intelligence (AI) inference engines, including those from Meta, Nvidia, Microsoft, ...
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 ...
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 ...
Abstract: Bayesian Neural Networks (BNNs) offer robust uncertainty estimation capabilities through probabilistic modeling, yet their prohibitively high computational complexity and resource ...
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