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

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

Graph Chatbot

Chattez avec Graph Search

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Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Towards a multiscale point cloud structural similarity metric

Positive Definite Completions and Continuous Graphical Models

Detecting whether a stochastic process is finitely expressed in a basis

Probing the nature of Dark Energy through the study of large scale structures using spectroscopic surveys and their simulations

Linear-Covariance Loss for End-to-End Learning of 6D Pose Estimation

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Distributional Regression and Autoregression via Optimal Transport

An equilibrated flux a posteriori error estimator for defeaturing problems