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Bayesian methods for nonparametric regression with neural networks

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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

Bayesian methods for nonparametric regression with neural networks

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

Random matrix methods for high-dimensional machine learning models

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

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

Distributional Regression and Autoregression via Optimal Transport

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

Robust discrete choice models with t-distributed kernel errors

DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

Distribution-on-distribution regression via optimal transport maps

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

Random matrix methods for high-dimensional machine learning models

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

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

Robust discrete choice models with t-distributed kernel errors

DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides