All Stories

  1. Reduced-order modeling for engineering systems: survey and opportunities for digital twins
  2. Parametric Operator Inference to Simulate the Purging Process in Semiconductor Manufacturing
  3. Physically consistent predictive reduced-order modeling by enhancing operator inference with state constraints
  4. Scalable computation of input-normal/output-diagonal balanced realization for control-affine polynomial systems
  5. Risk-based design optimization for powder bed fusion metal additive manufacturing
  6. Increasing certainty in systems biology models using Bayesian multimodel inference
  7. Conservative projection-based data-driven model order reduction of a fluid-kinetic spectral solver
  8. Systems modeling and uncertainty quantification of AMP-activated protein kinase signaling
  9. Scalable Computation of $\mathcal {H}_\infty$ Energy Functions for Polynomial Control-Affine Systems
  10. Robust design optimization with limited data for char combustion
  11. An Approximate Control Variates Approach to Multifidelity Distribution Estimation
  12. Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling
  13. Gradient preserving Operator Inference: Data-driven reduced-order models for equations with gradient structure
  14. Scalable computation of energy functions for nonlinear balanced truncation
  15. Increasing certainty in systems biology models using Bayesian multimodel inference
  16. Lagrangian operator inference enhanced with structure-preserving machine learning for nonintrusive model reduction of mechanical systems
  17. Exact and Optimal Quadratization of Nonlinear Finite-Dimensional Nonautonomous Dynamical Systems
  18. Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds
  19. Bayesian Inference and Global Sensitivity Analysis for Ambient Solar Wind Prediction
  20. Multifidelity conditional value-at-risk estimation by dimensionally decomposed generalized polynomial chaos-Kriging
  21. Bayesian parameter estimation for the inclusion of uncertainty in progressive damage simulation of composites
  22. Bayesian Inference and Global Sensitivity Analysis for Ambient Solar Wind Prediction
  23. Bi-fidelity conditional value-at-risk estimation by dimensionally decomposed generalized polynomial chaos expansion
  24. Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference
  25. Interpolatory Methods for Model Reduction [Bookshelf]
  26. Bayesian parameter estimation for dynamical models in systems biology
  27. Learning state variables for physical systems
  28. Bayesian Parameter Estimation for Dynamical Models in Systems Biology
  29. Hamiltonian operator inference: Physics-preserving learning of reduced-order models for canonical Hamiltonian systems
  30. Certifiable Risk-Based Engineering Design Optimization
  31. Balanced Reduced-Order Models for Iterative Nonlinear Control of Large-Scale Systems
  32. Stability Domains for Quadratic-Bilinear Reduced-Order Models
  33. Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms
  34. Learning Physics-Based Reduced-Order Models for a Single-Injector Combustion Process
  35. Multifidelity probability estimation via fusion of estimators
  36. Transform & Learn: A data-driven approach to nonlinear model reduction
  37. Nonlinear Model Order Reduction via Lifting Transformations and Proper Orthogonal Decomposition
  38. System Identification via CUR-Factored Hankel Approximation
  39. Multifidelity Preconditioning of the Cross-Entropy Method for Rare Event Simulation and Failure Probability Estimation
  40. Conditional-Value-at-Risk Estimation via Reduced-Order Models
  41. Learning-based robust stabilization for reduced-order models of 2D and 3D Boussinesq equations
  42. Combining multiple surrogate models to accelerate failure probability estimation with expensive high-fidelity models
  43. Robust POD model stabilization for the 3D Boussinesq equations based on Lyapunov theory and extremum seeking
  44. Sparse Sensing and DMD-Based Identification of Flow Regimes and Bifurcations in Complex Flows
  45. Feedback Control for Systems with Uncertain Parameters Using Online-Adaptive Reduced Models
  46. A POD projection method for large-scale algebraic Riccati equations
  47. Learning-based reduced order model stabilization for partial differential equations: Application to the coupled Burgers' equation
  48. Model reduction for control of a multiphysics system: Coupled Burgers' equation
  49. Tangential interpolation-based eigensystem realization algorithm for MIMO systems
  50. Full flux models for optimization and control of heat exchangers
  51. Solving Algebraic Riccati Equations via Proper Orthogonal Decomposition