37 citations · 43 across the 3 of their papers we have counts for
3 papers
A Sampling Strategy in Efficient Potential Energy Surface Mapping for Predicting Atomic Diffusivity in Crystals by Machine Learning
Kazuaki Toyoura, Takeo Fujii, Kenta Kanamori +1
We propose a machine-learning-based (ML-based) method for efficiently predicting atomic diffusivity in crystals, in which the potential energy surface (PES) of a diffusion carrier…
Variable Selection for Nonparametric Learning with Power Series Kernels
Kota Matsui, Wataru Kumagai, Kenta Kanamori +2
In this paper, we propose a variable selection method for general nonparametric kernel-based estimation. The proposed method consists of two-stage estimation: (1) construct a consi…
Exploring a potential energy surface by machine learning for characterizing atomic transport
Kenta Kanamori, Kazuaki Toyoura, Junya Honda +7
We propose a machine-learning method for evaluating the potential barrier governing atomic transport based on the preferential selection of dominant points for the atomic transport…