Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...
I have a real world project in the following scenario: I have a predefined network skeleton in DAG format. Our dataset has 1654 nodes, 2965 edges. I also have a dataset with shape (3000, 1654). Among ...
The mathematics that enable sensor fusion include probabilistic modeling and statistical estimation using Bayesian inference and techniques like particle filters, Kalman filters, and α-β-γ filters, ...
Abstract: This work studies an information-theoretic performance limit of an integrated sensing and communication (ISAC) system where the goal of sensing is to ...
Abstract: The Bayesian Cramér-Rao bound (CRB) provides a lower bound on the mean square error of any Bayesian estimator under mild regularity conditions. It can be ...
In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning method, ...
The folder contains examples and codes developed in the Willy Mutchler lecture's at the Tübingen University . The course deals with estimation of SVAR and DSGE models ...
Improving human motor performance via physical guidance by an assist robot device is a major field of interest of the society in many different contexts, such as rehabilitation and sports training. In ...
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