Name		Name	Last commit message	Last commit date
parent directory ..
configs		configs
README.md		README.md
base_problem.py		base_problem.py
base_solver.py		base_solver.py
controller.py		controller.py
data.py		data.py
deep_evolution_solver.py		deep_evolution_solver.py
deep_evolution_solver_test.py		deep_evolution_solver_test.py
domains.py		domains.py
requirements.txt		requirements.txt
run.py		run.py
run.sh		run.sh
simple_ising_model.py		simple_ising_model.py
simple_ising_model_test.py		simple_ising_model_test.py
utils.py		utils.py

README.md

Code related to Amortized Bayesian Optimization paper @ UAI2020 Conference

Contains implementation of learned evolutionary search, which can be run against the included example problems (ising models of different kinds).

Setup a virtual environment and run the solver using the provided run.sh:

sh amortized_bo/run.sh

This will dump the record of the run as /tmp/amortized_bo/experiment/population.csv

Reach out to ddohan@google.com with questions.