Publications related to MATHICSE Technical Report: A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

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Fast screening of covariates in population models empowered by machine learning

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A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

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We propose a non-intrusive reduced basis (RB) method for parametrized nonlinear partial differential equations (PDEs) that leverages models of different accuracy. From a collection of low-fidelity (LF) snapshots, parameter locations are extracted for the e ...

ELSEVIER SCIENCE SA2020

MATHICSE Technical Report: A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

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Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Distribution-on-distribution regression via optimal transport maps

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Fast screening of covariates in population models empowered by machine learning

Improving sample and feature selection with principal covariates regression

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Sparsest piecewise-linear regression of one-dimensional data

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Distributional Regression and Autoregression via Optimal Transport

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Distribution-on-distribution regression via optimal transport maps

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Fast screening of covariates in population models empowered by machine learning

Sparsest piecewise-linear regression of one-dimensional data

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Improving sample and feature selection with principal covariates regression

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems