This package uses an active learning approach to efficiently and confidently identify the Pareto front with any regression model that can output a mean and a standard deviation.
It works with any number of objectives, missing data, and is highly customizable.
If you find this code useful for your work, please cite:
Jablonka, K. M.; Giriprasad, M. J.; Wang, S.; Smit, B.; Yoo, B. De Novo Polymer Design with Multi Objective Active Learning and Molecular Simulations. 2020.
Zuluaga, M.; Krause, A.; Püschel, M. E-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem. Journal of Machine Learning Research 2016, 17 (104), 1–32.
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