主要発表論文
A02（コ）計画研究
A02（コ）計画研究 材料インフォマティクスに適した機械学習法の開拓
- M. Shiga, K. Tatsumi, S. Muto, K. Tsuda, Y. Yamamoto, T. Mori and T. Tanji, Sparse Modeling of EELS and EDX Spectral Imaging Data by Nonnegative Matrix Factorization. Ultramicroscopy 170, 43-59 (2016).
- I. Takigawa, K. Shimizu, K. Tsuda and S. Takakusagi, Machine-learning prediction of d-band center for metals and bimetals. RSC Advances 6, 52587-52595 (2016).
- T. Ueno, T.D. Rhone, Z. Hou, T. Mizoguchi and K. Tsuda, COMBO: An Efficient Bayesian Optimization Library for Materials Science. Materials Discovery 4, 18-21 (2016).
- H. Wang, H. Zhang, B. Da, M. Shiga, H. Kitazawa, D. Fujita, Informatics-Aided Raman Microscopy for Nanometric 3D Stress Characterization. Journal of Physical Chemistry C 122, 7187-7193 (2018)
- K. Kanamori, K. Toyoura, J. Honda, K. Hattori, A. Seko, M. Karasuyama, K. Shitara, M. Shiga, A. Kuwabara, I. Takeuchi, Exploring a potential energy surface by machine learning for characterizing atomic transport. Physical Review B 97, 125124 (2018)
- X. Yang, J. Zhang, K. Yoshizoe, K. Terayama and K. Tsuda, ChemTS: an efficient python library for de novo molecular generation. Science and Technology of Advanced Materials 18, 972-976, 2017.
- H. Oda, S. Kiyohara, K. Tsuda and T. Mizoguchi, Transfer Learning to Accelerate Interface Structure Searches. Journal of the Physical Society of Japan 86, 123601, 2017.
- T.M. Dieb, S. Ju, K. Yoshizoe, Z. Hou, J. Shiomi, K. Tsuda, MDTS: automatic complex materials design using Monte Carlo tree search. Science and Technology of Advanced Materials 18, 498-503, (2017).
