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IPAC'24 - 15th International Particle Accelerator Conference
IPAC'24 - 15th International Particle Accelerator Conference

19–24 May 2024
Music City Center
US/Central timezone
  • Overview
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Scientific Secretariat

  • scientific.secretariat@ipac24.org

Details for Alexander Scheinker

Los Alamos National Laboratory

Author in the following contributions

  • Utilizing neural networks to speed up coherent synchrotron radiation computations
  • Accelerator system parameter estimation using variational autoencoded latent regression
  • Solving the Orszag-Tang vortex magnetohydrodynamics problem with physics-constrained convolutional neural networks
  • Towards latent space evolution of spatiotemporal dynamics of six-dimensional phase space of charged particle beams
  • Generative deep learning for 6D phase space diagnostics via physics-constrained neural networks, physics models, and adaptive feedback
  • Estimation and control of accelerator beams by latent space tuning of generative models
  • Radiographic source prediction for linear induction accelerators using machine learning
  • Summary of the workshop on “UED opportunities for dynamical imaging of materials”
  • Early prediction of system failures at LANSCE
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