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Learning in Gaussian Markov random fields

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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

Learning in Gaussian Markov random fields

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Analysis-aware defeaturing of complex geometries with Neumann features

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Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

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From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

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Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Distributional Regression and Autoregression via Optimal Transport

An Unbiased Method of Measuring the Ratio of Two Data Sets

The elliptical Ornstein-Uhlenbeck process

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Distributional Regression and Autoregression via Optimal Transport

An Unbiased Method of Measuring the Ratio of Two Data Sets

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

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

Axial and radial axonal diffusivities and radii from single encoding strongly diffusion-weighted MRI

Data-driven modeling of beam loss in the LHC

Analysis-aware defeaturing of complex geometries with Neumann features

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering