Publications related to Multiple Kernel Learning: A Unifying Probabilistic Viewpoint

Distributional Regression and Autoregression via Optimal Transport

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

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

Distribution-on-distribution regression via optimal transport maps

Victor Panaretos, Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact interval. Our regression model is based on the theory of optimal transportation, and links the conditional Frechet mean of the resp ...

OXFORD UNIV PRESS2022

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

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

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

Online Robust Regression via SGD on the l1 loss

Nicolas Henri Bernard Flammarion, Scott William Pesme

We consider the robust linear regression problem in the online setting where we have access to the data in a streaming manner, one data point after the other. More specifically, for a true parameter , we consider the corrupted Gaussian linear model $ y=\la ...

2020

Bayesian regression explains how human participants handle parameter uncertainty

Michael Herzog, Jean-Pascal Théodor Pfister, Maya Anna Jastrzebowska, Mattew Pachai

Author summary How do humans make prediction when the critical factor that influences the quality of the prediction is hidden? Here, we address this question by conducting a simple psychophysical experiment in which participants had to extrapolate a parabo ...

2020

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

Anthony Christopher Davison, Jörg Hager, Hélène Ruffieux

We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, that is, predictors associated with several responses. Such a task is critical in statistical genetics, ...

INST MATHEMATICAL STATISTICS2020

Bayesian modeling of brain function and behavior

Maya Anna Jastrzebowska

The application of Bayesian modeling techniques is increasingly common in neuroscience due to the coherent and principled way in which the paradigm deals with uncertainty. The Bayesian framework is particularly valuable in the context of complex, ill-posed ...

EPFL2020

Multiple Kernel Learning: A Unifying Probabilistic Viewpoint

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Distributional Regression and Autoregression via Optimal Transport

Minimax rate for optimal transport regression between distributions

Distribution-on-distribution regression via optimal transport maps

Neural controlled differential equations for crop classification

Physics-enhanced machine learning with symmetry-adapted and long-range representations

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

Online Robust Regression via SGD on the l1 loss

Bayesian regression explains how human participants handle parameter uncertainty

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

Bayesian modeling of brain function and behavior

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

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

Neural controlled differential equations for crop classification

Bayesian regression explains how human participants handle parameter uncertainty

Minimax rate for optimal transport regression between distributions

Distributional Regression and Autoregression via Optimal Transport

Distribution-on-distribution regression via optimal transport maps

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Online Robust Regression via SGD on the l1 loss

Bayesian modeling of brain function and behavior