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On the sensitivity of buildings to climate

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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

On the sensitivity of buildings to climate

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Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

On distributional autoregression and iterated transportation

Distributional Regression and Autoregression via Optimal Transport

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

Robust discrete choice models with t-distributed kernel errors

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

A Study on Gradient-based Meta-learning for Robust Deep Digital Twins

EAST discharge prediction without integrating simulation results (vol 62, 126060, 2022)

Distribution-on-distribution regression via optimal transport maps

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

Distribution-on-distribution regression via optimal transport maps

EAST discharge prediction without integrating simulation results (vol 62, 126060, 2022)

Distributional Regression and Autoregression via Optimal Transport

On distributional autoregression and iterated transportation

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

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

A Study on Gradient-based Meta-learning for Robust Deep Digital Twins

Robust discrete choice models with t-distributed kernel errors