Data-driven deep learning of partial differential equations in modal space (Q2123370)

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scientific article; zbMATH DE number 7505629

Language	Label	Description	Also known as
English	Data-driven deep learning of partial differential equations in modal space	scientific article; zbMATH DE number 7505629

Statements

scholarly article

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Data-driven deep learning of partial differential equations in modal space (English)

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Journal of Computational Physics

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publication date

8 April 2022

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full work available at URL

https://arxiv.org/abs/1910.06948

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zbMATH Keywords

deep neural network

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residual network

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governing equation discovery

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modal space

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describes a project that uses

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MaRDI profile type

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Automated reverse engineering of nonlinear dynamical systems

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Discovering governing equations from data by sparse identification of nonlinear dynamical systems

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A machine learning approach for efficient uncertainty quantification using multiscale methods

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Solving high-dimensional partial differential equations using deep learning

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Solving many-electron Schrödinger equation using deep neural networks

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Non-intrusive reduced order modeling of nonlinear problems using neural networks

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Model selection for dynamical systems via sparse regression and information criteria

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Data driven governing equations approximation using deep neural networks

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Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

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Hidden physics models: machine learning of nonlinear partial differential equations

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Machine learning of linear differential equations using Gaussian processes

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An artificial neural network as a troubled-cell indicator

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Deep learning of dynamics and signal-noise decomposition with time-stepping constraints

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Learning partial differential equations via data discovery and sparse optimization

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Extracting Sparse High-Dimensional Dynamics from Limited Data

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Deep UQ: learning deep neural network surrogate models for high dimensional uncertainty quantification

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Numerical aspects for approximating governing equations using data

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Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification

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Identifiers

Mathematics Subject Classification ID

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zbMATH DE Number

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10.1016/J.JCP.2020.109307

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Sitelinks

Mathematics(1 entry)

mardi Publication:2123370

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