Publications associées à Point estimation

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction, and diffusion functions from the path of one single particle in the system. Our estimator is obtained by solving a linear sys ...

Siam Publications2024

A Shape Derivative Approach to Domain Simplification

Annalisa Buffa, Jochen Peter Hinz, Ondine Gabrielle Chanon, Alessandra Arrigoni

The objective of this study is to address the difficulty of simplifying the geometric model in which a differential problem is formulated, also called defeaturing, while simultaneously ensuring that the accuracy of the solution is maintained under control. ...

Oxford2023

Analysis-aware defeaturing of complex geometries with Neumann features

Pablo Antolin Sanchez, Ondine Gabrielle Chanon

Local modifications of a computational domain are often performed in order to simplify the meshing process and to reduce computational costs and memory requirements. However, removing geometrical features of a domain often introduces a non-negligible error ...

Hoboken2023

An equilibrated flux a posteriori error estimator for defeaturing problems

Annalisa Buffa, Denise Grappein, Rafael Vazquez Hernandez, Ondine Gabrielle Chanon

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

2023

The elliptical Ornstein-Uhlenbeck process

Sofia Charlotta Olhede

We introduce the elliptical Ornstein-Uhlenbeck (OU) process, which is a generalisation of the well-known univariate OU process to bivariate time series. This process maps out elliptical stochastic oscillations over time in the complex plane, which are obse ...

INT PRESS BOSTON, INC2023

ReLU Neural Network Galerkin BEM

Fernando José Henriquez Barraza

We introduce Neural Network (NN for short) approximation architectures for the numerical solution of Boundary Integral Equations (BIEs for short). We exemplify the proposed NN approach for the boundary reduction of the potential problem in two spatial dime ...

SPRINGER/PLENUM PUBLISHERS2023

Stereo Confidence Estimation via Locally Adaptive Fusion and Knowledge Distillation

Pascal Frossard, Seungryong Kim

Stereo confidence estimation aims to estimate the reliability of the estimated disparity by stereo matching. Different from the previous methods that exploit the limited input modality, we present a novel method that estimates confidence map of an initial ...

IEEE COMPUTER SOC2023

Analysis-aware defeaturing: Problem setting and a posteriori estimation

Annalisa Buffa, Rafael Vazquez Hernandez, Ondine Gabrielle Chanon

Defeaturing consists in simplifying geometrical models by removing the geometrical features that are considered not relevant for a given simulation. Feature removal and simplification of computer-aided design models enables faster simulations for engineeri ...

2022

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Point estimation

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

A Shape Derivative Approach to Domain Simplification

Analysis-aware defeaturing of complex geometries with Neumann features

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

An equilibrated flux a posteriori error estimator for defeaturing problems

The elliptical Ornstein-Uhlenbeck process

ReLU Neural Network Galerkin BEM

Stereo Confidence Estimation via Locally Adaptive Fusion and Knowledge Distillation

Methods of trajectory estimation in challenging mapping scenarios

Analysis-aware defeaturing: Problem setting and a posteriori estimation

Graph Chatbot

Chattez avec Graph Search

A Shape Derivative Approach to Domain Simplification

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

ReLU Neural Network Galerkin BEM

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

Analysis-aware defeaturing of complex geometries with Neumann features

Stereo Confidence Estimation via Locally Adaptive Fusion and Knowledge Distillation

Methods of trajectory estimation in challenging mapping scenarios

Analysis-aware defeaturing: Problem setting and a posteriori estimation

An equilibrated flux a posteriori error estimator for defeaturing problems

The elliptical Ornstein-Uhlenbeck process