Overcoming the curse of dimensionality in the numerical approximation of parabolic partial differential equations with gradient-dependent nonlinearities
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Publication:2162115
DOI10.1007/s10208-021-09514-yzbMath1501.65084arXiv1912.02571OpenAlexW2997339296WikidataQ115385125 ScholiaQ115385125MaRDI QIDQ2162115
Thomas Kruse, Martin Hutzenthaler, Arnulf Jentzen
Publication date: 5 August 2022
Published in: Foundations of Computational Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.02571
PDEpartial differential equationbackward stochastic differential equationcurse of dimensionalitymultilevel Monte CarloBSDEgradient-dependent nonlinearitymultilevel Picard
Monte Carlo methods (65C05) Heat equation (35K05) PDEs with randomness, stochastic partial differential equations (35R60) PDEs in connection with classical thermodynamics and heat transfer (35Q79) Probabilistic methods, particle methods, etc. for initial value and initial-boundary value problems involving PDEs (65M75)
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