Publications related to Framework for simulating deformable models and estimating their physical properties

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

Removing algorithmic discrimination (with minimal individual error)

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Le Nguyen Hoang

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

ELSEVIER2022

Removing Algorithmic Discrimination (With Minimal Individual Error)

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Le Nguyen Hoang

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

2022

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory

Maria-Alexandra Paun

It is shown that, in the framework of Scale Relativity Theory, correlations of type informational entropy/cross entropy - probability density, in the description of the dynamics of any complex system, can be perceived as interactions. Explaining these inte ...

UNIV POLITEHNICA BUCHAREST, SCI BULL2021

MATHICSE Technical Report : Density estimation in RKHS with application to Korobov spaces in high dimensions

Fabio Nobile, Yoshihito Kazashi

A kernel method for estimating a probability density function (pdf) from an i.i.d. sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined by a linear equation. An err ...

MATHICSE2021

On the density of the supremum of the solution to the linear stochastic heat equation

Robert Dalang, Fei Pu

We study the regularity of the probability density function of the supremum of the solution to the linear stochastic heat equation. Using a general criterion for the smoothness of densities for locally nondegenerate random variables, we establish the smoot ...

SPRINGER2020

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments

Paolo Perona, Giulio Calvani

The growth and establishment of riparian vegetation on river bedforms is of hydrological as well as ecological importance as it helps in enhancing spatial heterogeneity and thus the biodiversity of river corridors. Yet, during floods, flow drag and scourin ...

AGU2019

Global turbulence features across marginality and non-local pedestal-core interactions

Olivier Sauter, Laurent Villard, Stephan Brunner, Emmanuel Lanti, Alberto Bottino, Ben McMillan, Noé Thomas Elie Ohana

Spatially non-local aspects of turbulent transport in tokamak plasmas are examined with global gyrokinetic simulations using the ORB5 code. Inspired by very accurate measurements in the TCV tokamak in L-mode, we initialise plasma profiles with constant log ...

2019

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Fei Pu

In this thesis, we study systems of linear and/or non-linear stochastic heat equations and fractional heat equations in spatial dimension

1

driven by space-time white noise. The main topic is the study of hitting probabilities for the solutions to these ...

EPFL2018

Learning Search Strategies from Human Demonstrations

Guillaume Pierre Luc De Chambrier

Decision making and planning with partial state information is a problem faced by all forms of intelligent entities. The formulation of a problem under partial state information leads to an exorbitant set of choices with associated probabilistic outcomes m ...

EPFL2016

Framework for simulating deformable models and estimating their physical properties

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

Removing algorithmic discrimination (with minimal individual error)

Removing Algorithmic Discrimination (With Minimal Individual Error)

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory

MATHICSE Technical Report : Density estimation in RKHS with application to Korobov spaces in high dimensions

On the density of the supremum of the solution to the linear stochastic heat equation

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments

Global turbulence features across marginality and non-local pedestal-core interactions

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Learning Search Strategies from Human Demonstrations

Removing Algorithmic Discrimination (With Minimal Individual Error)

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

MATHICSE Technical Report : Density estimation in RKHS with application to Korobov spaces in high dimensions

Global turbulence features across marginality and non-local pedestal-core interactions

On the density of the supremum of the solution to the linear stochastic heat equation

Learning Search Strategies from Human Demonstrations

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Removing algorithmic discrimination (with minimal individual error)

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory