There are 3 repositories under latin-hypercube-sampling topic.
Provides a number of methods for creating and augmenting Latin Hypercube Samples and Orthogonal Array Latin Hypercube Samples
This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and multivariate) and use (1) Bayesian framework, (2) Pyomo package, (3) Genetic algorithm with local search, and (4) Pymoo package to find optimum design parameters and minimum energy consumption.
Latin hypercube sampling code for the lhs pacakge in the statistical software package R (www.r-project.org)
Simple implementation of Latin Hypercube Sampling.
Wrapper for sampling methods in R and approximate star discrepancy calculation
Implementation, analysis and benchmarking of optimization algorithms. Developed in Python and results showed in Jupyter Notebook
Optimization using MPI parallel Latin hypercube sampling and BOBYQA
Sampling and resampling techniques for random sample generation, estimation, and simulation
Hyperparameter tuning using a robust simulation optimization framework