Advances in plant imaging and computer vision have transformed agriculture and biology by enabling continuous and objective trait quantification. However, monitoring large plant populations or ...

A research team led by Prof. PAN Ding, Associate Professor from the Departments of Physics and Chemistry, and Dr. LI Shuo-Hui, Research Assistant Professor from the Department of Physics at the Hong ...

Bayesian statistics remain popular for addressing inverse problems, whereby quantities of interest are determined from their noisy and indirect observations. Bayes’ theorem forms the foundation of ...

Sampling from probability distributions with known density functions (up to normalization) is a fundamental challenge across various scientific domains. From Bayesian uncertainty quantification to ...

ABSTRACT: In this paper, a low-dose CT denoising method based on L 1 / L 2 regularization method of Markov chain Monte Carlo is studied. Firstly, the mathematical model and regularization method of ...

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 ...

Abstract: The efficiency of reliability simulation has long been a research hotspot. Crude Monte Carlo method is too time-consuming to analyze systems with long life and high reliability. In order to ...

Numerics is a free and open-source library for .NET developed by USACE-RMC, providing a comprehensive set of methods and algorithms for numerical computations and statistical analysis.