Conditioning by Adaptive Sampling for Robust Design

This repo contains the code for the paper:

D. H. Brookes, H. Park, and J. Listgarten. Conditioning by adaptive sampling for robust design. Proceedings of ICML, 2019.

The most important bits of code are in the files src/optimization_algs.py and notebooks/toy_conditioning.ipynb. In particular the function weighted_ml_opt in src/optimization_algs.py, with weights_type='cbas' runs the central CbAS method. Additionally, notebooks/toy_conditioning.ipynb, is a self-contained iPython notebook that runs the CbAS tests on the toy problem shown in Figure 1.