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Bayes estimator

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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

Bayes estimator

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Learning curves for the multi-class teacher-student perceptron

Regularization for distributionally robust state estimation and prediction

Functional data analysis with rough sample paths?

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Detecting whether a stochastic process is finitely expressed in a basis

Towards a multiscale point cloud structural similarity metric

ReLU Neural Network Galerkin BEM

Distributional Regression and Autoregression via Optimal Transport

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

Learning curves for the multi-class teacher-student perceptron

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Regularization for distributionally robust state estimation and prediction

Distributional Regression and Autoregression via Optimal Transport

Functional data analysis with rough sample paths?

ReLU Neural Network Galerkin BEM

Detecting whether a stochastic process is finitely expressed in a basis

Towards a multiscale point cloud structural similarity metric

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods