In my previous post “Bayesian Optimization”, I demonstrated the optimization procedure based on Bayesian method. However, Bayesian optimization has an issue of determining the initial samples in order ...

The design of sampling methods is crucial in digital soil mapping for soil organic carbon (SOC), as it directly affects prediction precision and reliability. While sampling methods based on ...

Just as its name implies, Monte Carlo Simulation is a mathematical technique that deals with randomness. This computational approach is used to model the probability of different outcomes in complex ...

Abstract: Large deviations theory is a well-studied area which has shown to have numerous applications. The typical results, however, assume that the underlying random variables are either i.i.d. or ...

This project is not actively worked on right now (May 2023). Until now only the two steps of the first stage of Park's algorithm are implemented. To Dos: Cleaning up the code, modularization More ...

SAR Sampling is designed to create realistic test scenarios for SAR testing by combining Latin Hypercube sampling with domain-specific knowledge about antenna configurations, frequency/radius mappings ...