3 papers
physics.chem-ph2022
MD-GAN with multi-particle input: the machine learning of long-time molecular behavior from short-time MD data
Ryo Kawada, Katsuhiro Endo, Daisuke Yuhara +1
MD-GAN is a machine learning-based method that can evolve part of the system at any time step, accelerating the generation of molecular dynamics data. For the accurate prediction o…
cs.CE2019
Dataflow programming for the analysis of molecular dynamics with AViS, an analysis and visualization software application
Kai Pua, Daisuke Yuhara, Sho Ayuba +1
The study of molecular dynamics simulations is largely facilitated by analysis and visualization toolsets. However, these toolsets are often designed for specific use cases and tho…
physics.comp-ph2019
Molecular Flow Monte Carlo
Katsuhiro Endo, Daisuke Yuhara, Kenji Yasuoka
In this paper, we suggest a novel sampling method for Monte Carlo molecular simulations. In order to perform efficient sampling of molecular systems, it is advantageous to avoid ex…