Active learning for adaptive surrogate model improvement in high-dimensional problems
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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Active learning for adaptive surrogate model improvement in high-dimensional problems ; volume:67 ; number:7 ; day:10 ; month:7 ; year:2024 ; pages:1-26 ; date:7.2024
Structural and multidisciplinary optimization ; 67, Heft 7 (10.7.2024), 1-26, 7.2024
- Creator
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Guo, Yulin
Nath, Paromita
Mahadevan, Sankaran
Witherell, Paul
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s00158-024-03816-9
- URN
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urn:nbn:de:101:1-2410242105492.093235508572
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:26 AM CEST
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Associated
- Guo, Yulin
- Nath, Paromita
- Mahadevan, Sankaran
- Witherell, Paul
- SpringerLink (Online service)
Other Objects (12)
Variable surrogate model-based particle swarm optimization for high-dimensional expensive problems
Surrogate modeling of high-dimensional vibroacoustic problems using parametric model order reduction
Spatially adaptive sparse grids for high-dimensional problems
Adaptive subspace methods for high-dimensional variable selection
Adaptive dropout for high-dimensional expensive multiobjective optimization
Adaptive bridge estimation for high-dimensional regression models
Adaptive concepts for high-dimensional stochastic differential equations
NATO-Übung ACTIVE IMPROVEMENT
Expected Improvement versus Predicted Value in Surrogate-Based Optimization
High-dimensional variable selection via low-dimensional adaptive learning
Entanglement protection of high-dimensional states by adaptive optics
Adaptive Bernstein change detector for high-dimensional data streams
Variable surrogate model-based particle swarm optimization for high-dimensional expensive problems
Surrogate modeling of high-dimensional vibroacoustic problems using parametric model order reduction
Spatially adaptive sparse grids for high-dimensional problems
Adaptive subspace methods for high-dimensional variable selection
Adaptive dropout for high-dimensional expensive multiobjective optimization
Adaptive bridge estimation for high-dimensional regression models
Adaptive concepts for high-dimensional stochastic differential equations
NATO-Übung ACTIVE IMPROVEMENT
Expected Improvement versus Predicted Value in Surrogate-Based Optimization
High-dimensional variable selection via low-dimensional adaptive learning
Entanglement protection of high-dimensional states by adaptive optics
Adaptive Bernstein change detector for high-dimensional data streams
Variable surrogate model-based particle swarm optimization for high-dimensional expensive problems
Surrogate modeling of high-dimensional vibroacoustic problems using parametric model order reduction
Spatially adaptive sparse grids for high-dimensional problems
Adaptive subspace methods for high-dimensional variable selection
Adaptive dropout for high-dimensional expensive multiobjective optimization
Adaptive bridge estimation for high-dimensional regression models
Adaptive concepts for high-dimensional stochastic differential equations
NATO-Übung ACTIVE IMPROVEMENT
Expected Improvement versus Predicted Value in Surrogate-Based Optimization
High-dimensional variable selection via low-dimensional adaptive learning
Entanglement protection of high-dimensional states by adaptive optics