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The impact of flood variables on riparian vegetation

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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

The impact of flood variables on riparian vegetation

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Chat with Graph Search

Distributional Regression and Autoregression via Optimal Transport

Acute TNF alpha levels predict cognitive impairment 6-9 months after COVID-19 infection

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

Distribution-on-distribution regression via optimal transport maps

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Learning Finance with Games: An Empirical Study

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

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Functional lagged regression with sparse noisy observations

Erosion processes of a novel configuration of sediment replenishment during an artificial flood

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

Learning Finance with Games: An Empirical Study

Acute TNF alpha levels predict cognitive impairment 6-9 months after COVID-19 infection

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Erosion processes of a novel configuration of sediment replenishment during an artificial flood

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

Functional lagged regression with sparse noisy observations