Code for the paper:

J. Mueller, D. N. Reshef, G. Du, and T. Jaakkola. Learning Optimal Interventions. AISTATS (2017).

Dependencies:

Our code requires numpy and scipy. You must also install the developer branch of the GPy package.
(At the time this code was developed, there was a bug in the predictive variances and gradients thereof in the non-developer version of GPy)

The main functions you can use to identify beneficial interventions from data are in:
PersonalizedIntervention.py (for individually-tailored interventions)
PopulationIntervention.py (for global shift or covariate-fixing policies)

A simple example showing the expected data-format and basic usage is given in: Examples.py