Publications related to Structured Dimensionality Reduction for Additive Model Regression

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

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

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

Scaling behavior of bedload transport: what if Bagnold was right?

Christophe Ancey

There is a paradox in the relationship between bedload transport rates and flow variables: laboratory and field studies have reported on how bedload transport rates depend on flow variables through a power law, but none of the empirical laws fitted to the ...

2023

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

Olga Fink, Ismail Nejjar

Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent works mostly focus on learning a deep feature encoder by minimizing the discrepa ...

IEEE2023

Minimax rate for optimal transport regression between distributions

Victor Panaretos, Laya Ghodrati

Distribution-on-distribution regression considers the problem of formulating and es-timating a regression relationship where both covariate and response are probability distributions. The optimal transport distributional regression model postulates that th ...

ELSEVIER2022

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - part 1: The dark side of peroxide

César Pulgarin, Stefanos Giannakis, Ling Feng

The present bi-partite work describes the development and validation of a mechanistic kinetic model of SODIS E. coli inactivation, enhanced with H2O2. In this first part, the mechanism of the baseline dark phenomena is modelled. A mechanistic model involvi ...

ELSEVIER SCIENCE SA2022

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Nikolaos Geroliminis, Emmanouil Barmpounakis

The work proposes a multi-modal regional mean speed regression analysis for the city network of Athens, Greece. The dataset from pNUEMA experiment is used in the present context. Accumulations and mean speeds of different modes are estimated and compared t ...

2021

Fast screening of covariates in population models empowered by machine learning

Jan Sickmann Hesthaven, Nadia Terranova

One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from supervise ...

2021

Improving sample and feature selection with principal covariates regression

Michele Ceriotti, Edgar Albert Engel, Benjamin Aaron Helfrecht, Sergei Kliavinek

Selecting the most relevant features and samples out of a large set of candidates is a task that occurs very often in the context of automated data analysis, where it improves the computational performance and often the transferability of a model. Here we ...

IOP PUBLISHING LTD2021

Neural controlled differential equations for crop classification

Accurate and scalable crop classification is important for food security and sustainable resources management. The temporal development of crops, i.e., their phenology, is a continuous phenomena that if properly captured, can help to discern them. The nove ...

2021

Structured Dimensionality Reduction for Additive Model Regression

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

Distributional Regression and Autoregression via Optimal Transport

Scaling behavior of bedload transport: what if Bagnold was right?

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

Minimax rate for optimal transport regression between distributions

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - part 1: The dark side of peroxide

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Fast screening of covariates in population models empowered by machine learning

Improving sample and feature selection with principal covariates regression

Neural controlled differential equations for crop classification

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

Distributional Regression and Autoregression via Optimal Transport

Minimax rate for optimal transport regression between distributions

Scaling behavior of bedload transport: what if Bagnold was right?

Improving sample and feature selection with principal covariates regression

Neural controlled differential equations for crop classification

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - part 1: The dark side of peroxide

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Fast screening of covariates in population models empowered by machine learning

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