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An unsupervised machine-learning checkpoint-restart algorithm using Gaussian mixtures for particle-in-cell simulations
We also ensure the preservation of Gauss' law after particle reconstruction.
Particle integrator for particle-in-cell simulations of ultra-high intensity laser-plasma interactions
Particle-in-cell codes are the most widely used simulation tools for kinetic studies of ultra-intense laser-plasma interactions.
Plasma Physics Computational Physics
An Adaptive EM Accelerator for Unsupervised Learning of Gaussian Mixture Models
We propose an Anderson Acceleration (AA) scheme for the adaptive Expectation-Maximization (EM) algorithm for unsupervised learning a finite mixture model from multivariate data (Figueiredo and Jain 2002).
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