Publications related to Non-parametric statistics

Density Estimation In Rkhs With Application To Korobov Spaces In High Dimensions

A kernel method for estimating a probability density function from an independent and identically distributed sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined b ...

SIAM PUBLICATIONS2023

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Thomas Gasos, Prateek Bansal

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Olga Fink, Tianfu Li

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Caroline Karmann, Bahar Aydemir, Kynthia Chamilothori, Seungryong Kim

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

Multisensing wearables for real-time monitoring of sweat electrolyte biomarkers during exercise and analysis on their correlation with core body temperature

Danick Briand, Silvia Demuru, Jaemin Kim, Brince Paul Kunnel, Vincent Gremeaux, Shu Wang

Sweat secreted by the human eccrine sweat glands can provide valuable biomarker information during exercise. Real-time non-invasive biomarker recordings are therefore useful for evaluating the physiological conditions of an athlete such as their hydration ...

2023

Towards a multiscale point cloud structural similarity metric

Touradj Ebrahimi

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

2023

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Giuseppe Carleo, Riccardo Rossi, Clemens Giuliani, Filippo Vicentini

Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statistical learning approach that makes the optimization trivial by using kernel me ...

Wien2023

Detecting whether a stochastic process is finitely expressed in a basis

Victor Panaretos, Neda Mohammadi Jouzdani

Is it possible to detect if the sample paths of a stochastic process almost surely admit a finite expansion with respect to some/any basis? The determination is to be made on the basis of a finite collection of discretely/noisily observed sample paths. We ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

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

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study

Bénédicte Marie Maréchal, Ricardo Alberto Corredor Jerez

Background: Small-vessel disease (SVD) plays a crucial role in cardiac and brain ischemia, but little is known about potential interrelation between both. We retrospectively evaluated 370 patients, aiming at assessing the interrelation between cardiac and ...

London2023

Non-parametric statistics

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Density Estimation In Rkhs With Application To Korobov Spaces In High Dimensions

Robust discrete choice models with t-distributed kernel errors

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Multisensing wearables for real-time monitoring of sweat electrolyte biomarkers during exercise and analysis on their correlation with core body temperature

Towards a multiscale point cloud structural similarity metric

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Detecting whether a stochastic process is finitely expressed in a basis

Distributional Regression and Autoregression via Optimal Transport

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Multisensing wearables for real-time monitoring of sweat electrolyte biomarkers during exercise and analysis on their correlation with core body temperature

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Towards a multiscale point cloud structural similarity metric

Distributional Regression and Autoregression via Optimal Transport

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study

Density Estimation In Rkhs With Application To Korobov Spaces In High Dimensions

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Robust discrete choice models with t-distributed kernel errors

Detecting whether a stochastic process is finitely expressed in a basis