Publications related to Sequential Outlier Detection Based on Incremental Decision Trees

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

Variational Inference with Mixture Model Approximation for Applications in Robotics

Sylvain Calinon, Emmanuel Pignat, Teguh Santoso Lembono

We propose to formulate the problem of repre-senting a distribution of robot configurations (e.g. joint angles)as that of approximating a product of experts. Our approach uses variational inference, a popular method in Bayesian computation, which has sever ...

2020

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Multimodal water age distributions and the challenge of complex hydrological landscapes

Paolo Benettin

Travel time distributions (TTDs) are concise descriptions of transport processes in catchments based on water ages, and they are particularly efficient as lumped hydrological models to simulate tracers in outflows. Past studies have approximated catchment ...

2020

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

The efficiency of stochastic particle schemes for large scale simulations relies on the ability to preserve a uniform distribution of particles in the whole physical domain. While simple particle split and merge algorithms have been considered previously, ...

2019

Comparing methodologies for structural identification and fatigue life prediction of a highway bridge

Ian Smith, Alain Nussbaumer, Sai Ganesh Sarvotham Pai

Accurate measurement-data interpretation leads to increased understanding of structural behavior and enhanced asset-management decision making. In this paper, four data-interpretation methodologies, residual minimization, traditional Bayesian model updatin ...

2018

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

Validation of likelihood ratio methods for forensic evidence evaluation handling multimodal score distributions

Rudolf Haraksim

This study presents a method for computing likelihood ratios (LRs) from multimodal score distributions, as the ones produced by some commercial off-the-shelf automated fingerprint identification systems (AFISs). The AFIS algorithms used to compare fingerma ...

Inst Engineering Technology-IET2017

An Application of Extreme Value Theory to Learning Analytics: Predicting Collaboration Outcome from Eye-tracking Data

Kshitij Sharma, Valérie Chavez

The statistics used in education research are based on central trends such as the mean or standard deviation, discarding outliers. This paper adopts another viewpoint that has emerged in Statistics, called the Extreme Value Theory (EVT). EVT claims that th ...

2017

Solving Stochastic AC Power Flow via Polynomial Chaos Expansion

Timm Faulwasser

The present contribution demonstrates the applicability of polynomial chaos expansion to stochastic (optimal) AC power flow problems that arise in the operation of power grids. For rectangular power flow, polynomial chaos expansion together with Galerkin p ...

IEEE2016

Sequential Outlier Detection Based on Incremental Decision Trees

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

Variational Inference with Mixture Model Approximation for Applications in Robotics

Wasserstein Distributionally Robust Learning

Multimodal water age distributions and the challenge of complex hydrological landscapes

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Comparing methodologies for structural identification and fatigue life prediction of a highway bridge

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

Validation of likelihood ratio methods for forensic evidence evaluation handling multimodal score distributions

An Application of Extreme Value Theory to Learning Analytics: Predicting Collaboration Outcome from Eye-tracking Data

Solving Stochastic AC Power Flow via Polynomial Chaos Expansion

Wasserstein Distributionally Robust Learning

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Multimodal water age distributions and the challenge of complex hydrological landscapes

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

Variational Inference with Mixture Model Approximation for Applications in Robotics

Solving Stochastic AC Power Flow via Polynomial Chaos Expansion

Comparing methodologies for structural identification and fatigue life prediction of a highway bridge

Validation of likelihood ratio methods for forensic evidence evaluation handling multimodal score distributions

An Application of Extreme Value Theory to Learning Analytics: Predicting Collaboration Outcome from Eye-tracking Data

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