136 citations · 364 across the 12 of their papers we have counts for
4 papers · 1 filter
Transfer learning with affine model transformation
Shunya Minami, Kenji Fukumizu, Yoshihiro Hayashi +1
Supervised transfer learning has received considerable attention due to its potential to boost the predictive power of machine learning in scenarios where data are scarce. Generall…
RadonPy: Automated Physical Property Calculation using All-atom Classical Molecular Dynamics Simulations for Polymer Informatics
Yoshihiro Hayashi, Junichiro Shiomi, Junko Morikawa +1
The rapid growth of data-driven materials research has made it necessary to develop systematically designed, open databases of material properties. However, there are few open data…
Bayesian Sequential Stacking Algorithm for Concurrently Designing Molecules and Synthetic Reaction Networks
Qi Zhang, Chang Liu, Stephen Wu +1
In the last few years, de novo molecular design using machine learning has made great technical progress but its practical deployment has not been as successful. This is mostly owi…
Crystal structure prediction with machine learning-based element substitution
Minoru Kusaba, Chang Liu, Ryo Yoshida
The prediction of energetically stable crystal structures formed by a given chemical composition is a central problem in solid-state physics. In principle, the crystalline state of…