Automatic detection of burst synchrony in preterm infants. - Alex Zwanenburg; Eduard Meijer; Ward Jennekens; Carola van Pul; Boris Kramer; Peter Andriessen (EMBC, 2012)

Full flux models for optimization and control of heat exchangers. - John A. Burns; Boris Kramer (ACC, 2015)

Learning-based reduced order model stabilization for partial differential equations: Application to the coupled Burgers' equation. - Mouhacine Benosman; Boris Kramer; Petros T. Boufounos; Piyush Grover (ACC, 2016)

Model reduction for control of a multiphysics system: Coupled Burgers' equation. - Boris Kramer (ACC, 2016)

Robust Reduced-Order Model Stabilization for Partial Differential Equations Based on Lyapunov Theory and Extremum Seeking with Application to the 3D Boussinesq Equations. - Mouhacine Benosman; Jeff Borggaard; Boris Kramer (CoRR, 2016)

Robust POD model stabilization for the 3D Boussinesq equations based on Lyapunov theory and extremum seeking. - Mouhacine Benosman; Jeff Borggaard; Boris Kramer (ACC, 2017)

Combining multiple surrogate models to accelerate failure probability estimation with expensive high-fidelity models. - Benjamin Peherstorfer; Boris Kramer; Karen Willcox (J. Comput. Phys., 2017)

Sparse Sensing and DMD-Based Identification of Flow Regimes and Bifurcations in Complex Flows. - Boris Kramer; Piyush Grover; Petros Boufounos; Saleh Nabi; Mouhacine Benosman (SIAM J. Appl. Dyn. Syst., 2017)

Feedback Control for Systems with Uncertain Parameters Using Online-Adaptive Reduced Models. - Boris Kramer; Benjamin Peherstorfer; Karen Willcox (SIAM J. Appl. Dyn. Syst., 2017)

Nonlinear Model Order Reduction via Lifting Transformations and Proper Orthogonal Decomposition. - Boris Kramer; Karen Willcox (CoRR, 2018)

Conditional-Value-at-Risk Estimation via Reduced-Order Models. - Matthias Heinkenschloss; Boris Kramer; Timur Takhtaganov; Karen Willcox (SIAM/ASA J. Uncertain. Quantification, 2018)

Multifidelity Preconditioning of the Cross-Entropy Method for Rare Event Simulation and Failure Probability Estimation. - Benjamin Peherstorfer; Boris Kramer; Karen Willcox (SIAM/ASA J. Uncertain. Quantification, 2018)

System Identification via CUR-Factored Hankel Approximation. - Boris Kramer; Alex A. Gorodetsky (SIAM J. Sci. Comput., 2018)

Balanced Truncation Model Reduction for Lifted Nonlinear Systems. - Boris Kramer; Karen E. Willcox (CoRR, 2019)

Learning physics-based reduced-order models for a single-injector combustion process. - Renee Swischuk; Boris Kramer; Cheng Huang; Karen Willcox (CoRR, 2019)

Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems. - Elizabeth Qian; Boris Kramer; Benjamin Peherstorfer; Karen Willcox (CoRR, 2019)

Multifidelity probability estimation via fusion of estimators. - Boris Kramer; Alexandre Noll Marques; Benjamin Peherstorfer; Umberto Villa; Karen Willcox (J. Comput. Phys., 2019)

Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms. - Peter Benner; Pawan Goyal 003; Boris Kramer; Benjamin Peherstorfer; Karen Willcox (CoRR, 2020)

Adaptive Reduced-Order Model Construction for Conditional Value-at-Risk Estimation. - Matthias Heinkenschloss; Boris Kramer; Timur Takhtaganov (SIAM/ASA J. Uncertain. Quantification, 2020)

Information Reuse for Importance Sampling in Reliability-Based Design Optimization. - Anirban Chaudhuri; Boris Kramer; Karen E. Willcox (Reliab. Eng. Syst. Saf., 2020)

Certifiable Risk-Based Engineering Design Optimization. - Anirban Chaudhuri; Boris Kramer; Matthew Norton 001; Johannes O. Royset; Karen Willcox (CoRR, 2021)

Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference. - Nihar Sawant; Boris Kramer; Benjamin Peherstorfer (CoRR, 2021)

Hamiltonian Operator Inference: Physics-preserving Learning of Reduced-order Models for Hamiltonian Systems. - Harsh Sharma; Zhu Wang 003; Boris Kramer (CoRR, 2021)

Balanced Reduced-Order Models for Iterative Nonlinear Control of Large-Scale Systems. - Yizhe Huang; Boris Kramer (IEEE Control. Syst. Lett., 2021)

Stability Domains for Quadratic-Bilinear Reduced-Order Models. - Boris Kramer (SIAM J. Appl. Dyn. Syst., 2021)

Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models. - Harsh Sharma; Nicholas Galioto; Alex A. Gorodetsky; Boris Kramer (CDC, 2022)

Preserving Lagrangian structure in data-driven reduced-order modeling of large-scale mechanical systems. - Harsh Sharma; Boris Kramer (CoRR, 2022)

Bi-fidelity conditional-value-at-risk estimation by dimensionally decomposed generalized polynomial chaos expansion. - Dongjin Lee; Boris Kramer (CoRR, 2022)

Learning state variables for physical systems. - Boris Kramer (Nat. Comput. Sci., 2022)

Bayesian parameter estimation for dynamical models in systems biology. - Nathaniel J. Linden; Boris Kramer; Padmini Rangamani (PLoS Comput. Biol., 2022)

Nonlinear Balanced Truncation: Part 2 - Model Reduction on Manifolds. - Boris Kramer; Serkan Gugercin; Jeff Borggaard (CoRR, 2023)

Exact and optimal quadratization of nonlinear finite-dimensional non-autonomous dynamical systems. - Andrey Bychkov; Opal Issan; Gleb Pogudin; Boris Kramer (CoRR, 2023)

Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds. - Harsh Sharma; Hongliang Mu; Patrick Buchfink; Rudy Geelen; Silke Glas; Boris Kramer (CoRR, 2023)

Global sensitivity analysis in the limited data setting with application to char combustion. - Dongjin Lee; Elle Lavichant; Boris Kramer (CoRR, 2023)

Predicting solar wind streams from the inner-heliosphere to Earth via shifted operator inference. - Opal Issan; Boris Kramer (J. Comput. Phys., 2023)

Correction: Bayesian parameter estimation for dynamical models in systems biology. - Nathaniel J. Linden; Boris Kramer; Padmini Rangamani (PLoS Comput. Biol., 2023)

Multifidelity conditional value-at-risk estimation by dimensionally decomposed generalized polynomial chaos-Kriging. - Dongjin Lee; Boris Kramer (Reliab. Eng. Syst. Saf., 2023)

Scalable Computation of $ mathcal{H}_{ infty}$ Energy Functions for Polynomial Drift Nonlinear Systems. - Nicholas A. Corbin; Boris Kramer (ACC, 2024)

Computing Solutions to the Polynomial-Polynomial Regulator Problem. - Nicholas A. Corbin; Boris Kramer (CDC, 2024)

Gradient Preserving Operator Inference: Data-Driven Reduced-Order Models for Equations with Gradient Structure. - Yuwei Geng; Jasdeep Singh; Lili Ju; Boris Kramer; Zhu Wang 003 (CoRR, 2024)

Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling. - Nicholas Galioto; Harsh Sharma; Boris Kramer; Alex Arkady Gorodetsky (CoRR, 2024)

Lagrangian operator inference enhanced with structure-preserving machine learning for nonintrusive model reduction of mechanical systems. - Harsh Sharma; David A. Najera-Flores; Michael D. Todd; Boris Kramer (CoRR, 2024)

Data-driven Model Reduction for Soft Robots via Lagrangian Operator Inference. - Harsh Sharma; Iman Adibnazari; Jacobo Cervera-Torralba; Michael Thomas Tolley; Boris Kramer (CoRR, 2024)

Anti-symmetric and positivity preserving formulation of a spectral method for Vlasov-Poisson equations. - Opal Issan; Oleksandr Koshkarov; Federico D. Halpern; Boris Kramer; Gian Luca Delzanno (J. Comput. Phys., 2024)

Global sensitivity analysis with limited data via sparsity-promoting D-MORPH regression: Application to char combustion. - Dongjin Lee; Elle Lavichant; Boris Kramer (J. Comput. Phys., 2024)

An Approximate Control Variates Approach to Multifidelity Distribution Estimation. - Ruijian Han; Boris Kramer; Dongjin Lee; Akil Narayan 001; Yiming Xu (SIAM/ASA J. Uncertain. Quantification, 2024)

Exact and Optimal Quadratization of Nonlinear Finite-Dimensional Nonautonomous Dynamical Systems. - Andrey Bychkov; Opal Issan; Gleb Pogudin; Boris Kramer (SIAM J. Appl. Dyn. Syst., 2024)

Conservative closures of the Vlasov-Poisson equations based on symmetrically weighted Hermite spectral expansion. - Opal Issan; Oleksandr Koshkarov; Federico D. Halpern; Boris Kramer; Gian Luca Delzanno (J. Comput. Phys., 2025)

Scalable computation of input-normal/output-diagonal balanced realization for control-affine polynomial systems. - Nicholas A. Corbin; Arijit Sarkar; Jacquelien M. A. Scherpen; Boris Kramer (Syst. Control. Lett., 2025)

Data-Driven Reduced-Order Models for Port-Hamiltonian Systems with Operator Inference. - Yuwei Geng; Lili Ju; Boris Kramer; Zhu Wang 003 (CoRR, 2025)

Physically consistent predictive reduced-order modeling by enhancing Operator Inference with state constraints. - Hyeonghun Kim; Boris Kramer (CoRR, 2025)

Discovering Polynomial and Quadratic Structure in Nonlinear Ordinary Differential Equations. - Boris Kramer; Gleb Pogudin (CoRR, 2025)

Nonlinear energy-preserving model reduction with lifting transformations that quadratize the energy. - Harsh Sharma; Juan Diego Draxl Giannoni; Boris Kramer (CoRR, 2025)

Parametric Operator Inference to Simulate the Purging Process in Semiconductor Manufacturing. - Seunghyon Kang; Hyeonghun Kim; Boris Kramer (CoRR, 2025)

Scalable Computation of $ mathcal {H}_ infty$ Energy Functions for Polynomial Control-Affine Systems. - Nicholas A. Corbin; Boris Kramer (IEEE Trans. Autom. Control., 2025)

Structure-preserving Lift & Learn: Scientific machine learning for nonlinear conservative partial differential equations. - Harsh Sharma; Juan Diego Draxl Giannoni; Boris Kramer (CoRR, 2025)

Weighted Proper Orthogonal Decomposition for High-Dimensional Optimization. - Sebastiaan P. C. van Schie; Boris Kramer; John T. Hwang (CoRR, 2025)