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Adaptive activation functions accelerate convergence in deep and physics-informed neural networks

Journal of computational physics, 2020-03, Vol.404 (C), p.109136, Article 109136

2020

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Machine learning of linear differential equations using Gaussian processes

Journal of computational physics, 2017-11, Vol.348, p.683-693

2017

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

Journal of computational physics, 2019-02, Vol.378, p.686-707

2019

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The scalar auxiliary variable (SAV) approach for gradient flows

Journal of computational physics, 2018-01, Vol.353, p.407-416

2018

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DGM: A deep learning algorithm for solving partial differential equations

Journal of computational physics, 2018-12, Vol.375, p.1339-1364

2018

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A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

Journal of computational physics, 2017-02, Vol.330 (C), p.192-220

2017

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PhyGeoNet: Physics-informed geometry-adaptive convolutional neural networks for solving parameterized steady-state PDEs on irregular domain

Journal of computational physics, 2021-03, Vol.428, p.110079, Article 110079

2021

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Linear, first and second-order, unconditionally energy stable numerical schemes for the phase field model of homopolymer blends

Journal of computational physics, 2016-12, Vol.327, p.294-316

Yang, Xiaofeng

2016

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A review of definitions of fractional derivatives and other operators

Journal of computational physics, 2019-07, Vol.388, p.195-208

2019

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Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

Journal of computational physics, 2015-03, Vol.285 (C), p.316-330

2015

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On the role of polynomials in RBF-FD approximations: I. Interpolation and accuracy

Journal of computational physics, 2016-09, Vol.321, p.21-38

2016

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Solving many-electron Schrödinger equation using deep neural networks

Journal of computational physics, 2019-12, Vol.399, p.108929, Article 108929

2019

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A family of high-order targeted ENO schemes for compressible-fluid simulations

Journal of computational physics, 2016-01, Vol.305, p.333-359

2016

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Atomic cluster expansion: Completeness, efficiency and stability

Journal of computational physics, 2022-04, Vol.454, p.110946, Article 110946

2022

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Comparative study on accuracy and conservation properties of two particle regularization schemes and proposal of an optimized particle shifting scheme in ISPH context

Journal of computational physics, 2017-03, Vol.332, p.236-256

2017

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Direct shape optimization through deep reinforcement learning

Journal of computational physics, 2021-03, Vol.428, p.110080, Article 110080

2021

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A generalized wall boundary condition for smoothed particle hydrodynamics

Journal of computational physics, 2012-08, Vol.231 (21), p.7057-7075

2012

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Inferring solutions of differential equations using noisy multi-fidelity data

Journal of computational physics, 2017-04, Vol.335, p.736-746

2017

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

Journal of computational physics, 2018-08, Vol.366, p.415-447

2018

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A novel evolutionary algorithm applied to algebraic modifications of the RANS stress–strain relationship

Journal of computational physics, 2016-11, Vol.325, p.22-37

2016

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Adaptive numerical algorithms in space weather modeling

Journal of computational physics, 2012-02, Vol.231 (3), p.870-903

2012

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A new fifth order finite difference WENO scheme for solving hyperbolic conservation laws

Journal of computational physics, 2016-08, Vol.318, p.110-121

2016

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Review of summation-by-parts schemes for initial–boundary-value problems

Journal of computational physics, 2014-07, Vol.268, p.17-38

2014

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Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations: A data-driven, physics-informed Bayesian approach

Journal of computational physics, 2016-11, Vol.324, p.115-136

2016

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Structural optimization under overhang constraints imposed by additive manufacturing technologies

Journal of computational physics, 2017-12, Vol.351, p.295-328

2017

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Adaptive activation functions accelerate convergence in deep and physics-informed neural networks

Machine learning of linear differential equations using Gaussian processes

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

The scalar auxiliary variable (SAV) approach for gradient flows

DGM: A deep learning algorithm for solving partial differential equations

A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

PhyGeoNet: Physics-informed geometry-adaptive convolutional neural networks for solving parameterized steady-state PDEs on irregular domain

Linear, first and second-order, unconditionally energy stable numerical schemes for the phase field model of homopolymer blends

A review of definitions of fractional derivatives and other operators

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

On the role of polynomials in RBF-FD approximations: I. Interpolation and accuracy

Solving many-electron Schrödinger equation using deep neural networks

A family of high-order targeted ENO schemes for compressible-fluid simulations

Atomic cluster expansion: Completeness, efficiency and stability

Comparative study on accuracy and conservation properties of two particle regularization schemes and proposal of an optimized particle shifting scheme in ISPH context

Direct shape optimization through deep reinforcement learning

A generalized wall boundary condition for smoothed particle hydrodynamics

Inferring solutions of differential equations using noisy multi-fidelity data

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

A novel evolutionary algorithm applied to algebraic modifications of the RANS stress–strain relationship

Adaptive numerical algorithms in space weather modeling

A new fifth order finite difference WENO scheme for solving hyperbolic conservation laws

Review of summation-by-parts schemes for initial–boundary-value problems

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations: A data-driven, physics-informed Bayesian approach

Structural optimization under overhang constraints imposed by additive manufacturing technologies

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