7 citations · 17 across the 15 of their papers we have counts for
Showing 2021 · physics.acc-phShow all
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physics.acc-ph2021★ 7 cited
Simulations of Future Particle Accelerators: Issues and Mitigations
D. Sagan, M. Berz, N. M. Cook +15
The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the succ…
physics.acc-ph2021★ 1 cited
Adaptive deep learning for time-varying systems with hidden parameters: Predicting changing input beam distributions of compact particle accelerators
Alexander Scheinker, Frederick Cropp, Sergio Paiagua +1
Machine learning (ML) tools such as encoder-decoder deep convolutional neural networks (CNN) are able to extract relationships between inputs and outputs of large complex systems d…