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Computer data analysis of the oscillating forward–reverse method

Journal of computational physics, 2012-06, Vol.231 (11), p.4355-4364

2012

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An automated analysis workflow for optimization of force-field parameters using neutron scattering data

Journal of computational physics, 2017-07, Vol.340 (C), p.128-137

2017

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Artificial neural network based response surface for data-driven dimensional analysis

Journal of computational physics, 2022-06, Vol.459, p.111145, Article 111145

2022

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A dynamic mode decomposition technique for the analysis of non–uniformly sampled flow data

Journal of computational physics, 2022-11, Vol.468, p.111495, Article 111495

2022

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Anomaly detection in scientific data using joint statistical moments

Journal of computational physics, 2019-06, Vol.387, p.522-538

2019

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Sequential function approximation with noisy data

Journal of computational physics, 2018-10, Vol.371, p.363-381

2018

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SAMBA: Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos

Journal of computational physics, 2016-09, Vol.320, p.1-16

2016

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A parallel and streaming Dynamic Mode Decomposition algorithm with finite precision error analysis for large data

Journal of computational physics, 2019-03, Vol.380, p.355-377

2019

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Data-driven eigensolution analysis based on a spatio-temporal Koopman decomposition, with applications to high-order methods

Journal of computational physics, 2022-01, Vol.449, p.110798, Article 110798

2022

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A fast and accurate algorithm for spherical harmonic analysis on HEALPix grids with applications to the cosmic microwave background radiation

Journal of computational physics, 2020-09, Vol.416, p.109544, Article 109544

2020

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Simple computational strategies for more effective physics-informed neural networks modeling of turbulent natural convection

Journal of computational physics, 2022-05, Vol.456, p.111022, Article 111022

2022

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Bayesian seismic inversion based on rock-physics prior modeling for the joint estimation of acoustic impedance, porosity and lithofacies

Journal of computational physics, 2017-05, Vol.336, p.128-142

2017

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Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis

Journal of computational physics, 2021-03, Vol.429, p.109999, Article 109999

2021

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Sparsity enabled cluster reduced-order models for control

Journal of computational physics, 2018-01, Vol.352, p.388-409

2018

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Continuous data assimilation for two-phase flow: Analysis and simulations

Journal of computational physics, 2022-10, Vol.466, p.111395, Article 111395

2022

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On the variational data assimilation problem solving and sensitivity analysis

Journal of computational physics, 2017-04, Vol.335, p.311-326

2017

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Flow feature detection for grid adaptation and flow visualization

Journal of computational physics, 2017-07, Vol.341, p.182-207

2017

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Data-driven Whitney forms for structure-preserving control volume analysis

Journal of computational physics, 2024-01, Vol.496, p.112520, Article 112520

2024

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Analysis of Admittance Data: Comparison of a Parametric and a Nonparametric Method

Journal of computational physics, 1999-07, Vol.153 (1), p.139-159

1999

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Computation of the analysis error covariance in variational data assimilation problems with nonlinear dynamics

Journal of computational physics, 2011-09, Vol.230 (22), p.7923-7943

2011

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Fast spin ±2 spherical harmonics transforms and application in cosmology

Journal of computational physics, 2007-10, Vol.226 (2), p.2359-2371

2007

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

Journal of computational physics, 2020-05, Vol.408, p.109307, Article 109307

2020

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Samplets: Construction and scattered data compression

Journal of computational physics, 2022-12, Vol.471, p.111616, Article 111616

2022

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A data-driven model reduction method for parabolic inverse source problems and its convergence analysis

Journal of computational physics, 2023-08, Vol.487, p.112156, Article 112156

2023

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Data-driven low-fidelity models for multi-fidelity Monte Carlo sampling in plasma micro-turbulence analysis

Journal of computational physics, 2022-02, Vol.451 (C), p.110898, Article 110898

2022

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Computer data analysis of the oscillating forward–reverse method

An automated analysis workflow for optimization of force-field parameters using neutron scattering data

Artificial neural network based response surface for data-driven dimensional analysis

A dynamic mode decomposition technique for the analysis of non–uniformly sampled flow data

Anomaly detection in scientific data using joint statistical moments

Sequential function approximation with noisy data

SAMBA: Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos

A parallel and streaming Dynamic Mode Decomposition algorithm with finite precision error analysis for large data

Data-driven eigensolution analysis based on a spatio-temporal Koopman decomposition, with applications to high-order methods

A fast and accurate algorithm for spherical harmonic analysis on HEALPix grids with applications to the cosmic microwave background radiation

Simple computational strategies for more effective physics-informed neural networks modeling of turbulent natural convection

Bayesian seismic inversion based on rock-physics prior modeling for the joint estimation of acoustic impedance, porosity and lithofacies

Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis

Sparsity enabled cluster reduced-order models for control

Continuous data assimilation for two-phase flow: Analysis and simulations

On the variational data assimilation problem solving and sensitivity analysis

Flow feature detection for grid adaptation and flow visualization

Data-driven Whitney forms for structure-preserving control volume analysis

Analysis of Admittance Data: Comparison of a Parametric and a Nonparametric Method

Computation of the analysis error covariance in variational data assimilation problems with nonlinear dynamics

Fast spin ±2 spherical harmonics transforms and application in cosmology

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

Samplets: Construction and scattered data compression

A data-driven model reduction method for parabolic inverse source problems and its convergence analysis

Data-driven low-fidelity models for multi-fidelity Monte Carlo sampling in plasma micro-turbulence analysis

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