Zobrazeno 1 - 10
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pro vyhledávání: '"the Taylor approximation"'
Score-based models, trained with denoising score matching, are remarkably effective in generating high dimensional data. However, the high variance of their training objective hinders optimisation. We attempt to reduce it with a control variate, deri
Externí odkaz:
http://arxiv.org/abs/2408.12270
Autor:
Nguyen, Cuong Duc
The development of disturbance estimators using extended state observers (ESOs) typically assumes that the system is observable. This paper introduces an improved method for systems that are initially unobservable, leveraging Taylor expansion to appr
Externí odkaz:
http://arxiv.org/abs/2405.02994
Autor:
Janssen, A. J. E. M.
Motivated by the needs in the theory of large deviations and in the theory of Lundberg's equation with heavy-tailed distribution functions, we study for $n=0,1,...$ the maximization of $S:~\Bigl(1-e^{-s}\Bigl(1+\frac{s^1}{1!}+...+\frac{s^n}{n!}\Bigr)
Externí odkaz:
http://arxiv.org/abs/2403.01940
Akademický článek
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Publikováno v:
journal = {Signal Processing}, pages = {108513}, year = {2022}, issn = {0165-1684}
The problem of off-grid direction-of-arrival (DOA) estimation is investigated. We develop a grid-based method to jointly estimate the closest spatial frequency (the sine of DOA) grids, and the gaps between the estimated grids and the corresponding fr
Externí odkaz:
http://arxiv.org/abs/2112.05487
Autor:
Chen, Peng, Ghattas, Omar
We propose a fast and scalable optimization method to solve chance or probabilistic constrained optimization problems governed by partial differential equations (PDEs) with high-dimensional random parameters. To address the critical computational cha
Externí odkaz:
http://arxiv.org/abs/2011.09985
Akademický článek
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Graph convolutional networks (GCN) have been recently utilized to extract the underlying structures of datasets with some labeled data and high-dimensional features. Existing GCNs mostly rely on a first-order Chebyshev approximation of graph wavelet-
Externí odkaz:
http://arxiv.org/abs/2007.00730
Publikováno v:
Геофизический журнал, Vol 45, Iss 5 (2023)
The seismic tomographic model obtained by the Taylor approximation method provides new constraints on the Earth’s crust and mantle structure beneath the Zagros mountain system at depths of 50—850 km. Based on structural geology and seismic tomogr
Externí odkaz:
https://doaj.org/article/1057a55a4cb04870ba680104a1bbd4a0
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 3, Pp 2650-2675 (2020)
Numerical approximation is a vital method to investigate the properties of stochastic age-dependent population systems, since most stochastic age-dependent population systems cannot be solved explicitly. In this paper, a Taylor approximation scheme f
Externí odkaz:
https://doaj.org/article/0b5e30fd8a484a7b9719624e0ea628cc