Sequential Learning of Active Subspaces
From MaRDI portal
Publication:5066503
DOI10.1080/10618600.2021.1874962OpenAlexW3122792075MaRDI QIDQ5066503
Nathan Wycoff, Stefan M. Wild, Mickaël Binois
Publication date: 29 March 2022
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1907.11572
Related Items (2)
Batch-sequential design and heteroskedastic surrogate modeling for delta smelt conservation ⋮ Multi‐fidelity data fusion through parameter space reduction with applications to automotive engineering
Uses Software
Cites Work
- Multi-Resolution Functional ANOVA for Large-Scale, Many-Input Computer Experiments
- Uncertainty management in simulation-optimization of complex systems. Algorithms and applications
- Gaussian processes with built-in dimensionality reduction: applications to high-dimensional uncertainty propagation
- Inverse regression-based uncertainty quantification algorithms for high-dimensional models: theory and practice
- Kriging surrogate model with coordinate transformation based on likelihood and gradient
- Additive covariance kernels for high-dimensional Gaussian process modeling
- ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis
- Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments
- A near-stationary subspace for ridge approximation
- Bayesian Optimization in a Billion Dimensions via Random Embeddings
- New sensitivity analysis subordinated to a contrast
- Active Subspaces
- Remark on “algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization”
- Estimating Derivatives of Noisy Simulations
- Exploring Regression Structure Using Nonparametric Functional Estimation
- Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods
- Sliced Inverse Regression for Dimension Reduction
- On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
- A Probabilistic Subspace Bound with Application to Active Subspaces
- Kernel Smoothing: Principles, Methods and Applications
- Modified Active Subspaces Using the Average of Gradients
- Sequential design of experiments for estimating percentiles of black-box functions
- A Review on Dimension Reduction
- Gradient-Based Kernel Dimension Reduction for Regression
- Derivative-free optimization methods
- Estimation of the Derivative-Based Global Sensitivity Measures Using a Gaussian Process Metamodel
- Data-Driven Polynomial Ridge Approximation Using Variable Projection
- Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Sequential Learning of Active Subspaces
