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Learning Finance with Games: An Empirical Study

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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

Learning Finance with Games: An Empirical Study

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Chat with Graph Search

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

Distributional Regression and Autoregression via Optimal Transport

Roles of Clinical Features and Chest CT in Predicting the Outcomes of Hospitalized Patients with COVID-19 Developing AKI

Hands-on reservoir computing: a tutorial for practical implementation

Distribution-on-distribution regression via optimal transport maps

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

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

Numerical investigation on the volute cutwater for pumps running in turbine mode

Functional lagged regression with sparse noisy observations

Structure-property maps with Kernel principal covariates regression

Roles of Clinical Features and Chest CT in Predicting the Outcomes of Hospitalized Patients with COVID-19 Developing AKI

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

Distributional Regression and Autoregression via Optimal Transport

Distribution-on-distribution regression via optimal transport maps

Hands-on reservoir computing: a tutorial for practical implementation

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

Numerical investigation on the volute cutwater for pumps running in turbine mode

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

Structure-property maps with Kernel principal covariates regression

Functional lagged regression with sparse noisy observations