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

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Alaya-in-Matrix/pyMACE

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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

About

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

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