UB Paderborn / Katalog / Suche / in CDI

Sortiert nach

Einfacher Volltextzugriff von (fast) überall

Installieren Sie die LibKey Nomad-Browsererweiterung und erhalten Sie von vielen Webseiten einfachen Zugriff auf lizenzierte Volltexte oder Open Access Publikationen. Mehr erfahren...

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

Nature communications, 2021-09, Vol.12 (1), p.5612-5612, Article 5612

2021

Volltextzugriff (PDF)

Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems

Physical review. Accelerators and beams, 2020-04, Vol.23 (4), p.044601, Article 044601

2020

Volltextzugriff (PDF)

Multiobjective Bayesian optimization for online accelerator tuning

Physical review. Accelerators and beams, 2021-06, Vol.24 (6), p.062801, Article 062801

2021

Volltextzugriff (PDF)

Multi-objective Bayesian active learning for MeV-ultrafast electron diffraction

Nature communications, 2024-06, Vol.15 (1), p.4726-4726

2024

Volltextzugriff (PDF)

Uncertainty quantification for deep learning in particle accelerator applications

Physical review. Accelerators and beams, 2021-11, Vol.24 (11), p.114601, Article 114601

2021

Volltextzugriff (PDF)

Bayesian Optimization for Multi-dimensional Alignment: Tuning Aberration Correctors and Ptychographic Reconstructions

Microscopy and microanalysis, 2022-08, Vol.28 (S1), p.3146-3148

2022

Volltextzugriff (PDF)

Advances in Machine Learning Based Modeling and Control of Particle Accelerators

Microscopy and microanalysis, 2021-08, Vol.27 (S1), p.808-808

Edelen, Auralee

2021

Volltextzugriff (PDF)

Demonstration of Autonomous Emittance Characterization at the Argonne Wakefield Accelerator

Instruments (Basel), 2023-09, Vol.7 (3), p.29

2023

Volltextzugriff (PDF)

Machine Learning for Design and Control of Particle Accelerators: A Look Backward and Forward

Annual review of nuclear and particle science, 2024-09, Vol.74 (1), p.557-581

2024

Volltextzugriff (PDF)

Efficient six-dimensional phase space reconstructions from experimental measurements using generative machine learning

Physical review. Accelerators and beams, 2024-09, Vol.27 (9), p.094601, Article 094601

2024

Volltextzugriff (PDF)

Bayesian optimization algorithms for accelerator physics

Physical review. Accelerators and beams, 2024-08, Vol.27 (8), p.084801, Article 084801

2024

Volltextzugriff (PDF)

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II

Information (Basel), 2021-02, Vol.12 (2), p.61

2021

Volltextzugriff (PDF)

Four-dimensional phase-space reconstruction of flat and magnetized beams using neural networks and differentiable simulations

Physical review. Accelerators and beams, 2024-07, Vol.27 (7), p.074601, Article 074601

2024

Volltextzugriff (PDF)

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives

Machine learning: science and technology, 2024-03, Vol.5 (1), p.15004

2024

Volltextzugriff (PDF)

Demonstration of Model-Independent Control of the Longitudinal Phase Space of Electron Beams in the Linac-Coherent Light Source with Femtosecond Resolution

Physical review letters, 2018-07, Vol.121 (4), p.044801-044801, Article 044801

2018

Volltextzugriff (PDF)

Adaptive model tuning studies for non-invasive diagnostics and feedback control of plasma wakefield acceleration at FACET-II

Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment, 2020-07, Vol.967 (C), p.163902, Article 163902

2020

Volltextzugriff (PDF)

Aberration Corrector Tuning with Machine-Learning-Based Emittance Measurements and Bayesian Optimization

Microscopy and microanalysis, 2021-08, Vol.27 (S1), p.810-812

2021

Volltextzugriff (PDF)

Physics-informed Bayesian Optimization of an Electron Microscope

Microscopy and microanalysis, 2023-07, Vol.29 (Supplement_1), p.1875-1877

2023

Volltextzugriff (PDF)

Improving surrogate model accuracy for the LCLS-II injector frontend using convolutional neural networks and transfer learning

Machine learning: science and technology, 2021-12, Vol.2 (4), p.45025

2021

Volltextzugriff (PDF)

Multipoint-BAX: A New Approach for Efficiently Tuning Particle Accelerator Emittance via Virtual Objectives

Machine learning: science and technology, 2023-12

2023

Volltextzugriff (PDF)

Neural Networks for Modeling and Control of Particle Accelerators

Edelen, Auralee Linscott

2020

Volltextzugriff (PDF)

Status and future plans for C3 R&D

Journal of instrumentation, 2023-09, Vol.18 (9), p.P09040

2023

Volltextzugriff (PDF)

Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems

Physical review. Accelerators and beams, 2020-04, Vol.23 (4)

2020

Volltextzugriff (PDF)

Status and future plans for C 3 R&D

Journal of instrumentation, 2023-09, Vol.18 (9), p.P09040

2023

Volltextzugriff (PDF)

1 – 25 von 25

Suche als RSS-Feed

Suchergebnisse filtern

Filter anzeigen

Nur zeigen

Geprüft (Peer-Review)
(24)
Mit Volltextzugriff
(24)

Publikationsform

Artikel
(24)
Dissertationen
(1)

Sprache

Englisch
(25)

Erscheinungsjahr

n.n

Thema

15 weitere anzeigen...

Weniger anzeigen...

Neu hinzugefügt

... seit 30 Tagen
(1)
... seit 90 Tagen
(2)

Menü

Weitere Dienste

Einstellungen

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems

Multiobjective Bayesian optimization for online accelerator tuning

Multi-objective Bayesian active learning for MeV-ultrafast electron diffraction

Uncertainty quantification for deep learning in particle accelerator applications

Bayesian Optimization for Multi-dimensional Alignment: Tuning Aberration Correctors and Ptychographic Reconstructions

Advances in Machine Learning Based Modeling and Control of Particle Accelerators

Demonstration of Autonomous Emittance Characterization at the Argonne Wakefield Accelerator

Machine Learning for Design and Control of Particle Accelerators: A Look Backward and Forward

Efficient six-dimensional phase space reconstructions from experimental measurements using generative machine learning

Bayesian optimization algorithms for accelerator physics

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II

Four-dimensional phase-space reconstruction of flat and magnetized beams using neural networks and differentiable simulations

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives

Demonstration of Model-Independent Control of the Longitudinal Phase Space of Electron Beams in the Linac-Coherent Light Source with Femtosecond Resolution

Adaptive model tuning studies for non-invasive diagnostics and feedback control of plasma wakefield acceleration at FACET-II

Aberration Corrector Tuning with Machine-Learning-Based Emittance Measurements and Bayesian Optimization

Physics-informed Bayesian Optimization of an Electron Microscope

Improving surrogate model accuracy for the LCLS-II injector frontend using convolutional neural networks and transfer learning

Multipoint-BAX: A New Approach for Efficiently Tuning Particle Accelerator Emittance via Virtual Objectives

Neural Networks for Modeling and Control of Particle Accelerators

Status and future plans for C3 R&D

Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems

Toward the end-to-end optimization of particle physics instruments with differentiable programming

Status and future plans for C 3 R&D

Suchergebnisse filtern