In mathematical modeling, the physical or geometrical parameters are often affected by uncertainties. For example, imperfections of an industrial manufacturing generate undesired variations in the produced devi
To estimate the model errors, we need a tentative mathematical modeling. Strategy and informativeness of the inverse problems depend on the dimensionality of models in use. The simplest inverse problem is 1-D inversion carried out in the class of 1-D models. It applies the mathematics of zero...
We formulate the inverse problem as a problem in optimization, where we define an objective function based on the data misfit and model regularization and aim to find a model which sufficiently minimizes it. Many variants of this are possible. At this stage of the workflow, all of the necessa...
The inverse topological problem at hand is to obtain the desired optical behavior: a target edge-state at frequency ωt, which is an input to the design (Fig. 2a). ML techniques achieve this result by modeling the multidimensional nonlinear relationships among all the structure parameters ωt,...
基于替换的方法:Song et al., "Score-Based Generative Modeling through Stochastic Differential Equations", ICLR 2021 Song et al., 即将每一个step重建后的结果和真实图像进行线性组合。 基于重构的方法:Chung et al., "Diffusion Posterior Sampling for General Noisy Inverse Problems", ICLR 2023 ...
n.反面;相反的事物 adj.反向的 v.使成反面 网络倒数;反选;反转 复数:inverses 同义词 反义词 adj. opposite,converse,reverse,contrary,other n. antithesis,flip side,counterpoint 权威英汉双解 英汉 英英 网络释义 inverse 显示所有例句 adj. 1. [obn] ...
of a reflective substrate. The computational effort using Fourier scatterometry at fixed wavelengths in comparison with our method is lower by the factor of the number of wavelengths used compared with the white light modeling using discrete wavelengths (see the section on ‘Model-based simulation’)...
{g}\)with maximal probability. This leads to the Bayesian perspective on inverse problem with the characteristic feature that prior to the measurements a probability distribution (the so-calledprior distribution) is assigned to the solution space\(\mathbb {X}\)modeling our prior knowledge on\(\...
Surrogate and Reduced‐Order Modeling: A Comparison of Approaches for Large‐Scale Statistical Inverse Problems Solution of statistical inverse problems via the frequentist or Bayesian approaches described in earlier chapters can be a computationally intensive endeav... BVB Waanders,M Frangos,YM Marzouk...
This level of efficiency is a result of combining the response feature technology with inverse modeling, in particular, establishing the model over low-dimensional operating condition space. The latter requires a limited number of samples to identify relationships between the operating frequency, power ...