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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

Graph Chatbot

Chattez avec 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

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

Distribution-on-distribution regression via optimal transport maps

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

Distributional Regression and Autoregression via Optimal Transport

Functional lagged regression with sparse noisy observations

Structure-property maps with Kernel principal covariates regression

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

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