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Robust compressive sensing of sparse signals: A review

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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

Robust compressive sensing of sparse signals: A review

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Chat with Graph Search

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

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

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Stability: a search for structure

Reliable data-driven decision-making through optimal transport

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Regularization for distributionally robust state estimation and prediction

Distributional Regression and Autoregression via Optimal Transport

An equilibrated flux a posteriori error estimator for defeaturing problems

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Stability: a search for structure

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

Reliable data-driven decision-making through optimal transport

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

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Regularization for distributionally robust state estimation and prediction

An equilibrated flux a posteriori error estimator for defeaturing problems

Distributional Regression and Autoregression via Optimal Transport