Výsledky vyhledávání - "high dimensional PDE"

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Physics-Informed Neural Networks with good lattice points set for solving low regularity PDEs and high dimensional PDE

Autor: Yang, Yu, He, PingAn, Peng, Xiaoling, He, Qiaolin

When dealing with a large number of points was required, the traditional uniform sampling approach for approximating integrals using the Monte Carlo method becomes inefficient. In this work, we leverage the good lattice point sets from number-theoret

Externí odkaz: http://arxiv.org/abs/2411.17039

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Akademický článek

Three-Layer Artificial Neural Network for Pricing Multi-Asset European Option

Autor: Zhiqiang Zhou, Hongying Wu, Yuezhang Li, Caijuan Kang, You Wu

Publikováno v: Mathematics, Vol 12, Iss 17, p 2770 (2024)

This paper studies an artificial neural network (ANN) for multi-asset European options. Firstly, a simple three-layer ANN-3 is established with undetermined weights and bias. Secondly, the time–space discrete PDE of the multi-asset option is given

Externí odkaz: https://doaj.org/article/a545144329a748c3bc370ddc9ee65c50

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Parameter Estimation for High-Dimensional PDE Models Using a Reduced Approach

Autor: Robert Kircheis, Stefan Körkel

Publikováno v: Contributions in Mathematical and Computational Sciences ISBN: 9783319233208

Partial differential equations (PDE) are indispensable to describe complex processes. PDE constrained parameter estimation is still a prevailing topic of research. The increase in computation time with increasing complexity of the problem is one of t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2ce70a83fe7055a93fcacf93fba0200d
https://doi.org/10.1007/978-3-319-23321-5_5

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Akademický článek

Study of Pricing of High-Dimensional Financial Derivatives Based on Deep Learning

Autor: Xiangdong Liu, Yu Gu

Publikováno v: Mathematics, Vol 11, Iss 12, p 2658 (2023)

Many problems in the fields of finance and actuarial science can be transformed into the problem of solving backward stochastic differential equations (BSDE) and partial differential equations (PDEs) with jumps, which are often difficult to solve in

Externí odkaz: https://doaj.org/article/dfc390aac4d5493a8af67d63cdcd8fdc

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Dissertation/ Thesis

Adaptive Solvers for High-Dimensional PDE Problems on Clusters of Multicore Processors

Autor: Grandin, Magnus

Accurate numerical solution of time-dependent, high-dimensional partial differential equations (PDEs) usually requires efficient numerical techniques and massive-scale parallel computing. In this thesis, we implement and evaluate discretization schem

Externí odkaz: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-234984

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Akademický článek

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Dissertation/ Thesis

Towards an adaptive solver for high-dimensional PDE problems on clusters of multicore processors

Autor: Gustafsson, Magnus

Accurate numerical simulation of time-dependent phenomena in many spatial dimensions is a challenging computational task apparent in a vast range of application areas, for instance quantum dynamics, financial mathematics, systems biology and plasma p

Externí odkaz: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-169259

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