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We present an algorithm for constructing efficient surrogate frequency-domain models of (nonlinear) parametric dynamical systems in a non-intrusive way. To capture the dependence of the underlying system on frequency and parameters, our proposed approach c ...
Production quality and process efficiency are the two main drivers that lead any industrial strategy. To ensure product quality, a duality historically existed between two approaches, namely batch sampling and systematic sampling. In batch sampling, the ba ...
This chapter takes stock of contemporary migration by breaking with a few myths and by distinguishing between interregional and international migration. It shows how new research paradigms have relativized the importance of the state as the preferred frame ...
Identifying multitarget impurities on contact lenses is challenging because traditional methods such as polymerase chain reaction cannot be used on the unknown target. Other sampling methods often require expensive antibodies or dyes. Therefore, this resea ...
We generalize the hidden-fermion family of neural network quantum states to encompass both continuous and discrete degrees of freedom and solve the nuclear many-body Schrodinger equation in a systematically improvable fashion. We demonstrate that adding hi ...
Background Neonatal hypothermia has been widely regarded as a major contributory factor to neonatal mortality and morbidity in low-resource settings. The high prevalence of potentially preventable hypothermia today urges an investigation into why neonates ...
The use of discrete choice models (DCMs) is a regular approach to investigating migration aspirations concerning destination choices. However, given the complex substitution patterns between destinations, more advanced model specifications than the multino ...
As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...
We study generalization properties of random features (RF) regression in high dimensions optimized by stochastic gradient descent (SGD) in under-/overparameterized regime. In this work, we derive precise non-asymptotic error bounds of RF regression under b ...
A proper assessment of technologies’ impact on energy consumption and GHG emissions is essential for designing an effective energy transition. In this regard, the modeling of an energy system is a great resource to identify valuable technologies. This pape ...