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Estimateur (statistique)

Publications associées (578)

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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

Estimateur (statistique)

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A Shape Derivative Approach to Domain Simplification

We Need Subject Matter Expertise to Choose and Identify Causal Estimands: Comment on "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event"

Analysis-aware defeaturing of complex geometries with Neumann features

Regularization for distributionally robust state estimation and prediction

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

Towards a multiscale point cloud structural similarity metric

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

Distributional Regression and Autoregression via Optimal Transport

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

Interpretable statistical representations of neural population dynamics and geometry

Towards a multiscale point cloud structural similarity metric

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

Distributional Regression and Autoregression via Optimal Transport

A Shape Derivative Approach to Domain Simplification

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

We Need Subject Matter Expertise to Choose and Identify Causal Estimands: Comment on "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event"

Interpretable statistical representations of neural population dynamics and geometry

Regularization for distributionally robust state estimation and prediction

Analysis-aware defeaturing of complex geometries with Neumann features

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