A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder
出版年份 2021 全文链接
标题
A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder
作者
关键词
Nonlinear manifold solution representation, Physics-informed neural network, Reduced order model, Nonlinear dynamical system, Hyper-reduction
出版物
JOURNAL OF COMPUTATIONAL PHYSICS
Volume 451, Issue -, Pages 110841
出版商
Elsevier BV
发表日期
2021-11-12
DOI
10.1016/j.jcp.2021.110841
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Gradient-based constrained optimization using a database of linear reduced-order models
- (2020) Youngsoo Choi et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations
- (2019) Christian Beck et al. JOURNAL OF NONLINEAR SCIENCE
- Space--Time Least-Squares Petrov--Galerkin Projection for Nonlinear Model Reduction
- (2019) Youngsoo Choi et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
- (2019) Yinhao Zhu et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
- (2019) Dongkun Zhang et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders
- (2019) Kookjin Lee et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Conservative model reduction for finite-volume models
- (2018) Kevin Carlberg et al. JOURNAL OF COMPUTATIONAL PHYSICS
- The Discrete Empirical Interpolation Method: Canonical Structure and Formulation in Weighted Inner Product Spaces
- (2018) Zlatko Drmač et al. SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS
- The Shifted Proper Orthogonal Decomposition: A Mode Decomposition for Multiple Transport Phenomena
- (2018) J. Reiss et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
- Transport Reversal for Model Reduction of Hyperbolic Partial Differential Equations
- (2018) Donsub Rim et al. SIAM-ASA Journal on Uncertainty Quantification
- DGM: A deep learning algorithm for solving partial differential equations
- (2018) Justin Sirignano et al. JOURNAL OF COMPUTATIONAL PHYSICS
- A unified deep artificial neural network approach to partial differential equations in complex geometries
- (2018) Jens Berg et al. NEUROCOMPUTING
- Solving high-dimensional partial differential equations using deep learning
- (2018) Jiequn Han et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Implementation and detailed assessment of a GNAT reduced-order model for subsurface flow simulation
- (2018) Rui Jiang et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
- (2018) M. Raissi et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Galerkin v. least-squares Petrov–Galerkin projection in nonlinear model reduction
- (2017) Kevin Carlberg et al. JOURNAL OF COMPUTATIONAL PHYSICS
- POD/DEIM Reduced-Order Modeling of Time-Fractional Partial Differential Equations with Applications in Parameter Identification
- (2017) Hongfei Fu et al. JOURNAL OF SCIENTIFIC COMPUTING
- POD-DEIM reduction of computational EMG models
- (2017) M. Mordhorst et al. Journal of Computational Science
- A New Selection Operator for the Discrete Empirical Interpolation Method---Improved A Priori Error Bound and Extensions
- (2016) Zlatko Drmač et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
- Fast Multiscale Reservoir Simulations With POD-DEIM Model Reduction
- (2016) Yanfang Yang et al. SPE JOURNAL
- A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems
- (2015) Peter Benner et al. SIAM REVIEW
- Adaptiveh-refinement for reduced-order models
- (2014) Kevin Carlberg INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
- Non-linear model reduction for the Navier–Stokes equations using residual DEIM method
- (2014) D. Xiao et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Design optimization using hyper-reduced-order models
- (2014) David Amsallem et al. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
- POD-DEIM Based Model Order Reduction for the Spherical Shallow Water Equations with Turkel-Zwas Finite Difference Discretization
- (2014) Pengfei Zhao et al. Journal of Applied Mathematics
- The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows
- (2013) Kevin Carlberg et al. JOURNAL OF COMPUTATIONAL PHYSICS
- POD/DEIM nonlinear model order reduction of an ADI implicit shallow water equations model
- (2012) R. Ştefănescu et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Efficient non-linear model reduction via a least-squares Petrov-Galerkin projection and compressive tensor approximations
- (2010) Kevin Carlberg et al. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
- Reduced order modeling based shape optimization of surface acoustic wave driven microfluidic biochips
- (2010) Harbir Antil et al. MATHEMATICS AND COMPUTERS IN SIMULATION
- Nonlinear Model Reduction via Discrete Empirical Interpolation
- (2010) Saifon Chaturantabut et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
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