A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs (Q6097873)

scientific article; zbMATH DE number 7693355

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English	A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs	scientific article; zbMATH DE number 7693355

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instance of

scholarly article

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title

A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs (English)

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zbMATH Open document ID

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SIAM Journal on Scientific Computing

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publication date

7 June 2023

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full work available at URL

https://arxiv.org/abs/2204.13454

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Mathematics Subject Classification ID

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reduced order models

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machine learning

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certified surrogate modeling

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MaRDI profile type

MaRDI publication profile

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OpenAlex ID

W4376128927

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cites work

Reduced basis methods with adaptive snapshot computations

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Q5060681

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Model Reduction and Approximation

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Applications

0 references

Model reduction of parametrized systems. Selected contributions based on the presentations at the MoRePaS conference, SISSA, Trieste, Italy, October 13--16, 2015

0 references

Optimization Methods for Large-Scale Machine Learning

0 references

ArbiLoMod: Local Solution Spaces by Random Training in Electrodynamics

0 references

6 Localized model reduction for parameterized problems

0 references

A Comparison Study of Deep Galerkin Method and Deep Ritz Method for Elliptic Problems with Different Boundary Conditions

0 references

Online Adaptive Basis Enrichment for Mixed CEM-GMsFEM

0 references

The Deep Ritz Method: a deep learning-based numerical algorithm for solving variational problems

0 references

DNN expression rate analysis of high-dimensional PDEs: application to option pricing

0 references

Q3446085

0 references

Kernel-based Approximation Methods using MATLAB

0 references

POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition

0 references

Implementing the Nelder-Mead simplex algorithm with adaptive parameters

0 references

A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows

0 references

Numerical solution of the parametric diffusion equation by deep neural networks

0 references

POD reduced-order modeling for evolution equations utilizing arbitrary finite element discretizations

0 references

<i>A posteriori</i>error bounds for reduced-basis approximations of parametrized parabolic partial differential equations

0 references

Reduced order modeling for nonlinear structural analysis using Gaussian process regression

0 references

Data-driven reduced order modeling for time-dependent problems

0 references

Convergence Rates of the POD–Greedy Method

0 references

Reduced basis method for finite volume approximations of parametrized linear evolution equations

0 references

A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics

0 references

Certified Reduced Basis Methods for Parametrized Partial Differential Equations

0 references

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

0 references

Hierarchical Approximate Proper Orthogonal Decomposition

0 references

A space-time certified reduced basis method for quasilinear parabolic partial differential equations

0 references

A successive constraint linear optimization method for lower bounds of parametric coercivity and inf-sup stability constants

0 references

Adaptive machine learning-based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery

0 references

A non-conforming dual approach for adaptive Trust-Region reduced basis approximation of PDE-constrained parameter optimization

0 references

Galerkin proper orthogonal decomposition methods for parabolic problems

0 references

A theoretical analysis of deep neural networks and parametric PDEs

0 references

Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

0 references

Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions

0 references

pyMOR -- Generic Algorithms and Interfaces for Model Order Reduction

0 references

Error Control for the Localized Reduced Basis Multiscale Method with Adaptive On-Line Enrichment

0 references

Optimal approximation of piecewise smooth functions using deep ReLU neural networks

0 references

A Certified Trust Region Reduced Basis Approach to PDE-Constrained Optimization

0 references

Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

0 references

Learning representations by back-propagating errors

0 references

Error analysis for physics-informed neural networks (PINNs) approximating Kolmogorov PDEs

0 references

Convergence rate of the data-independent $P$-greedy algorithm in kernel-based approximation

0 references

9 Kernel methods for surrogate modeling

0 references

Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations

0 references

Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem

0 references

Scattered Data Approximation

0 references

Physics-informed machine learning for reduced-order modeling of nonlinear problems

0 references

Analysis of target data-dependent greedy kernel algorithms: convergence rates for $f$-, $f \cdot P$- and $f/P$-greedy

0 references

Surrogate modeling of multiscale models using kernel methods

0 references

A Space-Time Petrov--Galerkin Certified Reduced Basis Method: Application to the Boussinesq Equations

0 references

A minimum-residual mixed reduced basis method: Exact residual certification and simultaneous finite-element reduced-basis refinement

0 references

A space-time hp-interpolation-based certified reduced basis method for Burgers' equation

0 references

Progressive construction of a parametric reduced‐order model for PDE‐constrained optimization

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mardi Publication:6097873