PROBABILISTIC APPROACH TO CHARACTERIZE QUANTITATIVE UNCERTAINTY IN NUMERICAL APPROXIMATIONS

DOI10.3846/13926292.2017.1272499zbMath1488.65606OpenAlexW2579746859MaRDI QIDQ5015439

Joël Chaskalovic, Franck Assous

Publication date: 8 December 2021

Published in: Mathematical Modelling and Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3846/13926292.2017.1272499

zbMATH Keywords

finite elementsdata miningbig dataprobabilistic modelsquantitative uncertainty

Mathematics Subject Classification ID

Inequalities; stochastic orderings (60E15) Probabilistic methods, particle methods, etc. for boundary value problems involving PDEs (65N75) General nonlinear regression (62J02) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30)

Related Items (3)

A new mixed functional-probabilistic approach for finite element accuracy ⋮ Explicit k-dependence for P_k finite elements in W^m,p error estimates: application to probabilistic laws for accuracy analysis ⋮ NUMERICAL VALIDATION OF PROBABILISTIC LAWS TO EVALUATE FINITE ELEMENT ERROR ESTIMATES

Uses Software

• Unnamed Item

Cites Work

• Mathematical and numerical methods for partial differential equations. Applications for engineering sciences
• Global a priori convergence theory for reduced-basis approximations of single-parameter symmetric coercive elliptic partial differential equations
• Indeterminate constants in numerical approximations of PDEs: a pilot study using data mining techniques
• An Introduction to Statistical Learning
• New development in freefem++
• Regression modeling strategies. With applications to linear models, logistic regression and survival analysis
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: PROBABILISTIC APPROACH TO CHARACTERIZE QUANTITATIVE UNCERTAINTY IN NUMERICAL APPROXIMATIONS