DAG-GP

Code for the paper Multi-task Causal Learning with Gaussian Processes (https://arxiv.org/pdf/2009.12821.pdf)

Usage

1. The code to run the DAG-GP model is in runCTF.py. The file runGPregression.py can be used to get results for the single-task GP models which are used as benchmarks in the paper.

2. The code for AL with the DAG-GP model is in runAL_CTF.py. The file runAL_reg.py can be used to get results for AL with single-task GP models which are used as benchmarks in the paper.

3. The code for running CBO with the DAG-GP model is in runCBO.py. By modifyng the value of the variable model_type one can change the surrogate GP model used in the algorith. When model_type==1 the DAG-GP model is used. When model_type==0 a single-task GP model is used.

For all experiments it is possible to change the causal graph that by changing the value of the variable experiment. In addition, it is possible to modify the GP prior used by changing the value of the variable causal_prior. The results are saved in the folder Data/ when running the experiments. The folder Data/ contains the observational and intervational data used to produce the results in the paper.

Contacts

Feel free to contact the first author of the paper (Virginia Aglietti) for questions