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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

ReLU Neural Network Galerkin BEM

Causal inference with recurrent and competing events

Reliable data-driven decision-making through optimal transport

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

Distributional Regression and Autoregression via Optimal Transport

Recovering Static and Time-Varying Communities Using Persistent Edges

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

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