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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

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

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

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