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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

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Graph Chatbot

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Reliable data-driven decision-making through optimal transport

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

Recovering Static and Time-Varying Communities Using Persistent Edges

Causal inference with recurrent and competing events

ReLU Neural Network Galerkin BEM

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

Distributional Regression and Autoregression via Optimal Transport

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

Regularization for distributionally robust state estimation and prediction

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

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

Reliable data-driven decision-making through optimal transport

Causal inference with recurrent and competing events

Distributional Regression and Autoregression via Optimal Transport

Regularization for distributionally robust state estimation and prediction

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

ReLU Neural Network Galerkin BEM

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Recovering Static and Time-Varying Communities Using Persistent Edges

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