PHYSBO Gallery
| About |
PHYSBO (optimization tools for PHYSics based on Bayesian Optimization) is a Python library for fast and scalable Bayesian optimization. It has been developed mainly for application in the basic sciences such as physics and materials science. Bayesian optimization is used to select an appropriate input for experiments/simulations from candidate inputs listed in advance in order to obtain better output values with the help of machine learning prediction. PHYSBO can be used to find better solutions for both single and multi-objective optimization problems. At each cycle in the Bayesian optimization, a single proposal or multiple proposals can be obtained for the next experiments/simulations. These proposals can be obtained interactively for use in experiments. PHYSBO is available at https://github.com/issp-center-dev/PHYSBO. This repository provides the sample data including input and output data for PHYSBO. |
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| URL | https://isspns-gitlab.issp.u-tokyo.ac.jp/physbo-dev/physbo-gallery |
| DOI | https://doi.org/10.1016/j.cpc.2022.108405 |
| Authors | Ryo Tamura , Yuichi Motoyama , Kazuyoshi Yoshimi , Kei Terayama , Tsuyoshi Ueno , Koji Tsuda |
| License | Documents: CC BY 4.0, Codes: GNU General Public License v3.0 or later |
| Category | Machine learning |
| References | Computer Physics Communications Volume 278, September 2022, 108405 |
| Related software | PHYSBO |
| Contact ※Please replace __at__ with @. |
physbo-dev__at__issp.u-tokyo.ac.jp |
| Note |