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Python implementation of the MACE Bayesian optimization algorithm, with GPy used as the backend GP library

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Name		Name	Last commit message	Last commit date
Latest commit History 32 Commits
circuit		circuit
.gitignore		.gitignore
GP.py		GP.py
MACE.py		MACE.py
README.md		README.md
conf.toml		conf.toml
main.py		main.py
obj.py		obj.py

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README

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The origin MACE algorithm, re-implemented in python

MCMC hyperparameter integration
Matern52 kernel

Dependencies

GPy for the GP regression
toml for config file
Platypus for multi-objective optimization

TODO

Improve the interface
Combine MACE with other parallel strategy like kriging believer or local penalization

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Python implementation of the MACE Bayesian optimization algorithm, with GPy used as the backend GP library

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