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A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

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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 Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Graph Chatbot

Chattez avec Graph Search

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Reliable data-driven decision-making through optimal transport

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Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

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Identifying genetic and dietary modulators of metabolic disorders using systems genetics

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Euclid preparation XXXVII. Galaxy colour selections with Euclid and ground photometry for cluster weak-lensing analyses

Reliable data-driven decision-making through optimal transport

At what spatial scale does natural selection operate? Using multiscale frameworks to calibrate the effects of environmental factors across landscape continuums

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Distributional Regression and Autoregression via Optimal Transport

Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Identifying genetic and dietary modulators of metabolic disorders using systems genetics

DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial