Presentation Information
[24p-P07-6]Improving the efficiency of searching for highly magnetic alloy materials using nonlinear dimensional compression methods and Bayesian optimization
〇Naoki Yoshida1, Yuma Iwasaki2, Yasuhiko Igarashi1 (1.Univ of Tsukuba, 2.NIMS)
Keywords:
Bayesian Optimization,VAE
In materials informatics, Bayesian optimization is often used to search for alloy materials with high functional properties. In this study, we efficiently performed a Bayesian optimization search by reducing the dimensionality of the material search space, which is becoming increasingly high-dimensional, using deep generative learning and nonlinear dimension reduction techniques. In this presentation, we will visualize the search space for alloy materials and discuss how dimensionality reduction techniques affect Bayesian optimization.