Hint
Example code: https://github.com/cselab/korali/tree/master/examples/learning/surrogates/optimization/
Optimization on Surrogates with Gaussian ProcessesΒΆ
This tutorial shows how to use a korali surrogate as a model for optimization.
The file train-surrogate.py
constructs a Gaussian Process surrogate fronm the given synthetic data and saves it inside the _korali_result_surrogate/
folder.
Second, we load and use the trained surrogate as a function to optimize.
This is done in run-cmaes.py
.