Projection pursuit adaptation on polynomial chaos expansions (Q2683425)

scientific article; zbMATH DE number 7653047

Language	Label	Description	Also known as
English	Projection pursuit adaptation on polynomial chaos expansions	scientific article; zbMATH DE number 7653047

Statements

instance of

scholarly article

0 references

title

Projection pursuit adaptation on polynomial chaos expansions (English)

0 references

0 references

0 references

Computer Methods in Applied Mechanics and Engineering

0 references

publication date

10 February 2023

0 references

full work available at URL

https://arxiv.org/abs/2211.13420

0 references

zbMATH Keywords

surrogate modeling

0 references

polynomial chaos expansion

0 references

projection pursuit

0 references

high-dimensional models

0 references

dimension reduction

0 references

data-driven

0 references

describes a project that uses

0 references

0 references

0 references

0 references

0 references

Propagation of probabilistic uncertainty in complex physical systems using a stochastic finite element approach

0 references

Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics

0 references

Uncertainty quantification. An accelerated course with advanced applications in computational engineering

0 references

Stochastic spectral methods for efficient Bayesian solution of inverse problems

0 references

Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems

0 references

Q5268658

0 references

Ingredients for a general purpose stochastic finite elements implementation

0 references

The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations

0 references

Modeling uncertainty in steady state diffusion problems via generalized polynomial chaos

0 references

Multi-output local Gaussian process regression: applications to uncertainty quantification

0 references

Stochastic Dynamics of Structures

0 references

Probabilistic learning on manifolds constrained by nonlinear partial differential equations for small datasets

0 references

Stochastic modeling of geometrical uncertainties on complex domains, with application to additive manufacturing and brain interface geometries

0 references

Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold

0 references

Addressing the curse of dimensionality in stochastic dynamics: a Wiener path integral variational formulation with free boundaries

0 references

A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

0 references

Spectral Methods for Uncertainty Quantification

0 references

Q5600030

0 references

Numerical integration using sparse grids

0 references

Simple cubature formulas with high polynomial exactness

0 references

Adaptive sparse polynomial chaos expansion based on least angle regression

0 references

A non-adapted sparse approximation of PDEs with stochastic inputs

0 references

DIMENSIONALITY REDUCTION FOR COMPLEX MODELS VIA BAYESIAN COMPRESSIVE SENSING

0 references

Compressive sampling of polynomial chaos expansions: convergence analysis and sampling strategies

0 references

Active Subspace Methods in Theory and Practice: Applications to Kriging Surfaces

0 references

Active Subspaces

0 references

Basis adaptation in homogeneous chaos spaces

0 references

Accelerated basis adaptation in homogeneous chaos spaces

0 references

Machine learning. A probabilistic perspective

0 references

A Projection Pursuit Algorithm for Exploratory Data Analysis

0 references

Projection pursuit

0 references

Exploratory Projection Pursuit

0 references

Bayesian neural networks for uncertainty quantification in data-driven materials modeling

0 references

B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data

0 references

Functional projection pursuit regression

0 references

Remarks on a Multivariate Transformation

0 references

Gaussian Hilbert Spaces

0 references

Optimal weighted least-squares methods

0 references

Sparse tensor discretizations of high-dimensional parametric and stochastic PDEs

0 references

Reduced Wiener chaos representation of random fields via basis adaptation and projection

0 references

Bayesian Design and Analysis of Computer Experiments: Use of Derivatives in Surface Prediction

0 references

The Elements of Statistical Learning

0 references

Identifiers

Mathematics Subject Classification ID

0 references

0 references

0 references

0 references

10.1016/J.CMA.2022.115845

0 references

Sitelinks

Mathematics(1 entry)

mardi Publication:2683425