Python implementation of the classical and quantum-inspired Single-Thread Monte Carlo algorithm for estimating ground state energies, using a transformation matrix to improve convergence.

In the evening rain, the Perelman Center shimmers like a sturgeon. In the architectural hodgepodge of the former World Trade Center — hard by Santiago Calatrava’s bony Oculus, just opposite Michael ...

1 Graduate School of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan 2 Research Organization of Science and Technology, Ritsumeikan University, Kusatsu, Japan The main ...

ABSTRACT: This paper proposes a Full Range Gaussian Markov Random Field (FRGMRF) model for monochrome image compression, where images are assumed to be Gaussian Markov Random Field. The parameters of ...

Abstract: Metropolis-Hastings algorithm (MH) is the most popular Markov Chain Monte Carlo (MCMC) method. Essentially, the MH algorithm generates a sample, accepts or rejects the sample based on an ...

Abstract: The paper studies the features of the Metropolis-Hastings algorithm and its applications in Bayesian data analysis problems. The application of the Monte-Carlo Markov chains (MCMC) methods ...

In the first semester of my MSc. studies, we developed a phyton version of the Gibbs Sampler and Metropolis-Hastings Algorithm from the scratch. We described our results and analysis in a report.

Many computational problems in modern-day statistics are heavily dependent on Markov chain Monte Carlo (MCMC) methods. These algorithms allow us to evaluate arbitrary probability distributions; ...

ABSTRACT: In this paper, we study some robustness aspects of linear regression models of the presence of outliers or discordant observations considering the use of stable distributions for the ...

This work presents a version of the Metropolis–Hastings algorithm using quasi-Monte Carlo inputs. We prove that the method yields consistent estimates in some problems with finite state spaces and ...