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Real-Time Multi-Ion-Monitoring Front-End With Interference Compensation by Multi-Output Support Vector Regressor

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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

Real-Time Multi-Ion-Monitoring Front-End With Interference Compensation by Multi-Output Support Vector Regressor

Graph Chatbot

Chattez avec Graph Search

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

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Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

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

Distributional Regression and Autoregression via Optimal Transport

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Random matrix methods for high-dimensional machine learning models

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

Distributional Regression and Autoregression via Optimal Transport

Intraday solar irradiance forecasting using public cameras

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

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination