Bayesian Optimization and Design of Experiments
Design-of-experiment (DOE) generator for science, engineering, and statistics
Design of Experiment Generator. Read the docs at: https://doepy.readthedocs.io/en/latest/
Framework for Data-Driven Design & Analysis of Structures & Materials (F3DASM)
Generates and evaluates D, I, A, Alias, E, T, G, and custom optimal designs. Supports generation and evaluation of mixture and split/split-split/N-split plot designs. Includes parametric and Monte Carlo power evaluation functions. Provides a framework to evaluate power using functions provided in other packages or written by the user.
Experimental design and Bayesian optimization library in Python/PyTorch
Design of Experiments in Julia
Curated list of resources for the Design of Experiments (DOE)
BASM - 2017 Spring
python experiment management toolset
Python library for Design and Analysis of Experiments
Python package for flexible generation of D-optimal experimental designs
Design of Experiments and Analysis
A tool for remote experiment management
Blocking and randomization for experimental design
Simulation and Analysis Tool for TAP Reactor Systems
Open-source constructor of surrogates and metamodels
Accelerate 2024 Workshop on Bayesian Optimization Recipes With BayBE
Simple implementation of Latin Hypercube Sampling.
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