Our approach models label noise in semantic segmentation with a probabilistic framework that incorporates spatial correlations. By introducing a continuous latent ...

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1 Department of Statistics, School of Mathematics, University of Leeds, Leeds, United Kingdom 2 Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of ...

Landslide susceptibility assessment is crucial to mitigate the severe impacts of landslides. Although Bayesian network (BN) has been widely used in landslide susceptibility assessment, no study has ...

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, ...

Abstract: An improved approximate Bayesian combined with Markov Chain Monte Carlo method for solving probabilistic power flow (PPF) is proposed for the stochastic and intermittent nature of scenic ...

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

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 ...

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