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- W3202283410 abstract "Uncertainty quantification under process variations is an important topic in computational electromagnetics (EM) and electronic design automation (EDA). The popular stochastic methods become computationally inefficient when the number of uncertain parameters grows. A promising technique to address this challenge is tensor computation. This short paper reviews some recent tensor methods for high-dimensional uncertainty quantification in the field of EDA and computational EM." @default.
- W3202283410 created "2021-10-11" @default.
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- W3202283410 date "2021-08-01" @default.
- W3202283410 modified "2023-09-23" @default.
- W3202283410 title "Progress of Tensor-Based High-Dimensional Uncertainty Quantification of Process Variations" @default.
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- W3202283410 doi "https://doi.org/10.1109/aces53325.2021.00020" @default.
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