An implementation of the paper "NeuralBO: A black-box optimization algorithm using deep neural networks".
This is an official implementation of paper "NeuralBO: A black-box optimization algorithm using deep neural networks" published at Neurocomputing journal.
- This work was tested with PyTorch 2.0.1, CUDA 11.7, python 3.11.5
conda install pytorch cudatoolkit=11.7 -c pytorch
python main.py -cfg <path_to_config_file>
To define your new objective function, please consider the example Ackley function in utils/objective.py.
To plot the minimum values found by the algorithm, use utils/plot_min_values.py To plot the minimal points chosen at each optimization step, use utils/visualization.py
Please consider citing this work in your publications if it helps your research.
@article{phan2023neuralbo,
title={NeuralBO: A black-box optimization algorithm using deep neural networks},
author={Phan-Trong, Dat and Tran-The, Hung and Gupta, Sunil},
journal={Neurocomputing},
volume={559},
pages={126776},
year={2023},
publisher={Elsevier}
}