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

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Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

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

Graph Chatbot

Chattez avec Graph Search

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

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

Distributional Regression and Autoregression via Optimal Transport

Improving sample and feature selection with principal covariates regression

Sparsest piecewise-linear regression of one-dimensional data

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

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

Distribution-on-distribution regression via optimal transport maps

Fast screening of covariates in population models empowered by machine learning

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

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