| Publication | Date of Publication | Type |
|---|
| A digital twin framework for civil engineering structures | 2024-03-25 | Paper |
| Improving the accuracy and scalability of large-scale physics-based data-driven reduced modeling via domain decomposition | 2023-11-01 | Paper |
| Nonintrusive Reduced-Order Models for Parametric Partial Differential Equations via Data-Driven Operator Inference | 2023-08-17 | Paper |
| Learning latent representations in high-dimensional state spaces using polynomial manifold constructions | 2023-06-23 | Paper |
| Multi-output multilevel best linear unbiased estimators via semidefinite programming | 2023-06-19 | Paper |
| Learning physics-based models from data: perspectives from inverse problems and model reduction | 2023-04-14 | Paper |
| Bayesian operator inference for data-driven reduced-order modeling | 2023-01-19 | Paper |
| Learning high-dimensional parametric maps via reduced basis adaptive residual networks | 2023-01-19 | Paper |
| Balanced Truncation Model Reduction for Lifted Nonlinear Systems | 2022-11-11 | Paper |
| A MATHEMATICAL AND COMPUTATIONAL FRAMEWORK FOR MULTIFIDELITY DESIGN AND ANALYSIS WITH COMPUTER MODELS | 2022-11-04 | Paper |
| Stress-constrained topology optimization of lattice-like structures using component-wise reduced order models | 2022-10-10 | Paper |
| Reduced Operator Inference for Nonlinear Partial Differential Equations | 2022-07-13 | Paper |
| Stress-constrained topology optimization of lattice-like structures using component-wise reduced order models | 2022-05-19 | Paper |
| Operator inference for non-intrusive model reduction with quadratic manifolds | 2022-05-04 | Paper |
| Bayesian operator inference for data-driven reduced-order modeling | 2022-04-22 | Paper |
| Lift \& learn: physics-informed machine learning for large-scale nonlinear dynamical systems | 2022-03-17 | Paper |
| Non-intrusive data-driven model reduction for differential-algebraic equations derived from lifting transformations | 2022-01-26 | Paper |
| Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive Residual Networks | 2021-12-13 | Paper |
| Conditional reliability analysis in high dimensions based on controlled mixture importance sampling and information reuse | 2021-10-26 | Paper |
| A multifidelity method for a nonlocal diffusion model | 2021-10-19 | Paper |
| Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms | 2021-04-26 | Paper |
| Reduced operator inference for nonlinear partial differential equations | 2021-01-29 | Paper |
| Multifidelity probability estimation via fusion of estimators | 2021-01-26 | Paper |
| Multifidelity Dimension Reduction via Active Subspaces | 2020-04-28 | Paper |
| Model adaptivity for goal-oriented inference using adjoints | 2020-04-06 | Paper |
| Data-driven operator inference for nonintrusive projection-based model reduction | 2020-03-30 | Paper |
| Hessian‐based model reduction: large‐scale inversion and prediction | 2020-02-18 | Paper |
| Multifidelity importance sampling | 2019-05-17 | Paper |
| Projection-based model reduction: formulations for physics-based machine learning | 2019-04-26 | Paper |
| Dynamic data-driven reduced-order models | 2019-03-27 | Paper |
| Conditional-Value-at-Risk Estimation via Reduced-Order Models | 2019-01-21 | Paper |
| Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization | 2018-08-14 | Paper |
| Nonlinear Model Order Reduction via Lifting Transformations and Proper Orthogonal Decomposition | 2018-08-06 | Paper |
| Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices | 2018-07-19 | Paper |
| Multifidelity Preconditioning of the Cross-Entropy Method for Rare Event Simulation and Failure Probability Estimation | 2018-07-19 | Paper |
| Convergence analysis of multifidelity Monte Carlo estimation | 2018-07-16 | Paper |
| Geometric Subspace Updates with Applications to Online Adaptive Nonlinear Model Reduction | 2018-03-02 | Paper |
| Combining multiple surrogate models to accelerate failure probability estimation with expensive high-fidelity models | 2017-12-15 | Paper |
| Goal-Oriented Optimal Approximations of Bayesian Linear Inverse Problems | 2017-10-27 | Paper |
| A Certified Trust Region Reduced Basis Approach to PDE-Constrained Optimization | 2017-10-27 | Paper |
| Data-Driven Reduced Model Construction with Time-Domain Loewner Models | 2017-10-04 | Paper |
| Feedback Control for Systems with Uncertain Parameters Using Online-Adaptive Reduced Models | 2017-08-24 | Paper |
| Missing Point Estimation in Models Described by Proper Orthogonal Decomposition | 2017-08-08 | Paper |
| Optimal \(L_2\)-norm empirical importance weights for the change of probability measure | 2017-06-30 | Paper |
| Minimum local distance density estimation | 2017-04-27 | Paper |
| Multifidelity approaches for optimization under uncertainty | 2016-12-30 | Paper |
| A decomposition‐based approach to uncertainty analysis of feed‐forward multicomponent systems | 2016-12-30 | Paper |
| Data-driven model reduction for the Bayesian solution of inverse problems | 2016-12-30 | Paper |
| Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction | 2016-12-05 | Paper |
| Optimal Model Management for Multifidelity Monte Carlo Estimation | 2016-10-12 | Paper |
| An Accelerated Greedy Missing Point Estimation Procedure | 2016-09-23 | Paper |
| A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems | 2016-05-20 | Paper |
| Book Reviews | 2016-05-20 | Paper |
| A Domain Decomposition Approach for Uncertainty Analysis | 2015-11-27 | Paper |
| Online Adaptive Model Reduction for Nonlinear Systems via Low-Rank Updates | 2015-09-21 | Paper |
| Nonlinear Goal-Oriented Bayesian Inference: Application to Carbon Capture and Storage | 2014-09-05 | Paper |
| Localized Discrete Empirical Interpolation Method | 2014-05-26 | Paper |
| Constrained multifidelity optimization using model calibration | 2013-11-15 | Paper |
| Goal-Oriented Inference: Approach, Linear Theory, and Application to Advection Diffusion | 2013-09-26 | Paper |
| Goal-Oriented Inference: Approach, Linear Theory, and Application to Advection Diffusion | 2012-10-26 | Paper |
| https://portal.mardi4nfdi.de/entity/Q3172610 | 2011-10-05 | Paper |
| Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems | 2011-06-10 | Paper |
| Interpolation among reduced‐order matrices to obtain parameterized models for design, optimization and probabilistic analysis | 2010-04-21 | Paper |
| Non‐linear model reduction for uncertainty quantification in large‐scale inverse problems | 2010-04-09 | Paper |
| Real-time optimization using proper orthogonal decomposition: free surface shape prediction due to underwater bubble dynamics | 2009-12-07 | Paper |
| Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space | 2009-11-27 | Paper |
| Krylov projection framework for Fourier model reduction | 2008-03-18 | Paper |
| Unsteady flow sensing and estimation via the gappy proper orthogonal decomposition | 2006-10-20 | Paper |
| https://portal.mardi4nfdi.de/entity/Q5701667 | 2005-11-04 | Paper |
| Controllable and Observable Subspaces in Computational Fluid Dynamics | 2005-03-30 | Paper |
| Fourier Series for Accurate, Stable, Reduced-Order Models in Large-Scale Linear Applications | 2005-02-25 | Paper |
