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Fast characterization of input-output behavior of non-charge-based logic devices by machine learning
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Data-efficient machine learning for physics-based simulations
(2019) -
Machine learning for fast characterization of magnetic logic devices
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- Journal Article
- A1
- open access
Review of polynomial chaos-based methods for uncertainty quantification in modern integrated circuits
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- Journal Article
- A1
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A Kriging and stochastic collocation ensemble for uncertainty quantification in engineering applications
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- Journal Article
- A1
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Measurement uncertainty propagation in transistor model parameters via polynomial chaos expansion
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- Conference Paper
- C3
- open access
Comparison study of PC and kriging based surrogate modeling
(2016) p.1-1