Markov Chain Monte Carlo (MCMC) methods have become indispensable in contemporary statistical science, enabling researchers to approximate complex probability distributions that are otherwise ...

A landmark global modeling study reveals that more than 2.8 billion people in 104 countries are at risk of chikungunya, with ...

In this paper, we propose a probabilistic approach to finding failure-causing inputs based on Bayesian estimation. According to our probabilistic insights of software testing, the test case generation ...

Markov Chain Monte Carlo (MCMC) originated in statistical physics, but has spilled over into various application areas, leading to a corresponding variety of techniques and methods. That variety ...

We present a Bayesian Monte Carlo Markov Chain method to simultaneously estimate the spectral index and power amplitude of a fractional differenced Gaussian process at low frequency, in presence of ...

Stochastic image denoising based on Markov-chain Monte Carlo sampling. Title: Stochastic image denoising based on Markov-chain Monte Carlo sampling: Author: Alexander Wong. Akshaya Mishra. Wen Zhang.