Citation

Open Code and Citation

GPyOpt is free and runs under BSD 3-clause license. We are happy to developing it for you but if you use it please please cite

@Misc{gpyopt2016,
  author =   {The GPyOpt authors},
  title =    {GPyOpt: A Bayesian Optimization framework in Python},
  howpublished = {\url{http://github.com/SheffieldML/GPyOpt}},
  year = {2016}
}

References

GPyOpt contains many general and well known Bayesian optimization options but it also offers you to use our last work in the field. GPyOpt is also based on:

• Javier González, Michael Osborne and Neil D. Lawrence. GLASSES: Relieving The Myopia Of Bayesian Optimisation.Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 790–799, 2016.

• Javier González, Zhenwen Dai, Philipp Hennig and Neil D. Lawrence. Batch Bayesian Optimization via Local Penalization. Optimisation*.Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), pp 648–657, 2016.

• Javier González, Joseph Longworth, David James, Neil Lawrence. Bayesian Optimization for synthetic gene design. The Neural Information Processing Systems (NIPS’14), Workshop in Bayesian Optimization, 2014.

Please cite these works if you use any of the methods mentioned above.