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A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

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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

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Graph Chatbot

Chattez avec Graph Search

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Stability: a search for structure

Distributional Regression and Autoregression via Optimal Transport

Regularization for distributionally robust state estimation and prediction

Alpha-NML Universal Predictors

Distribution-on-distribution regression via optimal transport maps

Minimax rate for optimal transport regression between distributions

Gait-dependent Traversability Estimation on the k-rock2 Robot

Parametric Estimation For Functional Autoregressive Processes On The Sphere

Stability: a search for structure

Distributional Regression and Autoregression via Optimal Transport

Distribution-on-distribution regression via optimal transport maps

Parametric Estimation For Functional Autoregressive Processes On The Sphere

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set

Alpha-NML Universal Predictors

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Regularization for distributionally robust state estimation and prediction

Minimax rate for optimal transport regression between distributions

Gait-dependent Traversability Estimation on the k-rock2 Robot