Abstract: Naïve Bayesian inference enables classification or prediction of an event given observations of potentially contradictory evidences, and is particularly intriguing in power-limited contexts ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

Perceptual judgments of ambiguous stimuli are often biased by prior expectations. These biases may offer a window into the neural computations that give rise to perceptual interpretations of the ...

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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, ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including ...

1 Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands 2 Department of Engineering, King’s College London, London, United Kingdom Simulation is an ...