230 citations · 230 across the 1 of their papers we have counts for
5 papers
Machine learning force fields and coarse-grained variables in molecular dynamics: application to materials and biological systems
Paraskevi Gkeka, Gabriel Stoltz, Amir Barati Farimani +14
Machine learning encompasses a set of tools and algorithms which are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as…
Transferability of Operational Status Classification Models Among Different Wind Turbine Typesq
Z. Trstanova, A. Martinsson, C. Matthews +4
A detailed understanding of wind turbine performance status classification can improve operations and maintenance in the wind energy industry. Due to different engineering properti…
TATi-Thermodynamic Analytics ToolkIt: TensorFlow-based software for posterior sampling in machine learning applications
Frederik Heber, Zofia Trstanova, Benedict Leimkuhler
With the advent of GPU-assisted hardware and maturing high-efficiency software platforms such as TensorFlow and PyTorch, Bayesian posterior sampling for neural networks becomes pla…
Local and Global Perspectives on Diffusion Maps in the Analysis of Molecular Systems
Zofia Trstanova, Ben Leimkuhler, Tony Lelièvre
Diffusion maps approximate the generator of Langevin dynamics from simulation data. They afford a means of identifying the slowly-evolving principal modes of high-dimensional molec…
Diffusion maps tailored to arbitrary non-degenerate Ito processes
Ralf Banisch, Zofia Trstanova, Andreas Bittracher +2
We present two generalizations of the popular diffusion maps algorithm. The first generalization replaces the drift term in diffusion maps, which is the gradient of the sampling de…