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ORCIDBoris Kramer
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2020 – today
- 2024
[j19]Dongjin Lee
, Elle Lavichant, Boris Kramer:
Global sensitivity analysis with limited data via sparsity-promoting D-MORPH regression: Application to char combustion. J. Comput. Phys. 511: 113116 (2024)- [j18]Opal Issan, Oleksandr Koshkarov, Federico D. Halpern, Boris Kramer, Gian Luca Delzanno:
Anti-symmetric and positivity preserving formulation of a spectral method for Vlasov-Poisson equations. J. Comput. Phys. 514: 113263 (2024) - [j17]Andrey Bychkov, Opal Issan, Gleb Pogudin, Boris Kramer:
Exact and Optimal Quadratization of Nonlinear Finite-Dimensional Nonautonomous Dynamical Systems. SIAM J. Appl. Dyn. Syst. 23(1): 982-1016 (2024) - [c8]Nicholas A. Corbin, Boris Kramer:
Scalable Computation of $\mathcal{H}_{\infty}$ Energy Functions for Polynomial Drift Nonlinear Systems. ACC 2024: 2521-2526 - [i25]Yuwei Geng, Jasdeep Singh, Lili Ju, Boris Kramer, Zhu Wang:
Gradient Preserving Operator Inference: Data-Driven Reduced-Order Models for Equations with Gradient Structure. CoRR abs/2401.12138 (2024) - [i24]Nicholas Galioto, Harsh Sharma, Boris Kramer, Alex Arkady Gorodetsky:
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling. CoRR abs/2401.12476 (2024) - [i23]Harsh Sharma, David A. Najera-Flores, Michael D. Todd, Boris Kramer:
Lagrangian operator inference enhanced with structure-preserving machine learning for nonintrusive model reduction of mechanical systems. CoRR abs/2404.05040 (2024) - [i22]Harsh Sharma, Iman Adibnazari, Jacobo Cervera-Torralba, Michael Thomas Tolley, Boris Kramer:
Data-driven Model Reduction for Soft Robots via Lagrangian Operator Inference. CoRR abs/2407.08840 (2024) - 2023
- [j16]Opal Issan, Boris Kramer:
Predicting solar wind streams from the inner-heliosphere to Earth via shifted operator inference. J. Comput. Phys. 473: 111689 (2023) - [j15]Nathaniel J. Linden, Boris Kramer, Padmini Rangamani:
Correction: Bayesian parameter estimation for dynamical models in systems biology. PLoS Comput. Biol. 19(4) (2023) - [j14]Dongjin Lee, Boris Kramer:
Multifidelity conditional value-at-risk estimation by dimensionally decomposed generalized polynomial chaos-Kriging. Reliab. Eng. Syst. Saf. 235: 109208 (2023) - [i21]Boris Kramer, Serkan Gugercin, Jeff Borggaard:
Nonlinear Balanced Truncation: Part 2 - Model Reduction on Manifolds. CoRR abs/2302.02036 (2023) - [i20]Andrey Bychkov, Opal Issan, Gleb Pogudin, Boris Kramer:
Exact and optimal quadratization of nonlinear finite-dimensional non-autonomous dynamical systems. CoRR abs/2303.10285 (2023) - [i19]Harsh Sharma, Hongliang Mu, Patrick Buchfink, Rudy Geelen, Silke Glas, Boris Kramer:
Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds. CoRR abs/2305.15490 (2023) - [i18]Dongjin Lee, Elle Lavichant, Boris Kramer:
Global sensitivity analysis in the limited data setting with application to char combustion. CoRR abs/2307.07486 (2023) - [i17]Opal Issan, Oleksandr Koshkarov, Federico D. Halpern, Boris Kramer, Gian Luca Delzanno:
Anti-symmetric and Positivity Preserving Formulation of a Spectral Method for Vlasov-Poisson Equations. CoRR abs/2312.05439 (2023) - 2022
- [j13]Boris Kramer:
Learning state variables for physical systems. Nat. Comput. Sci. 2(7): 414-415 (2022) - [j12]Nathaniel J. Linden, Boris Kramer, Padmini Rangamani:
Bayesian parameter estimation for dynamical models in systems biology. PLoS Comput. Biol. 18(10): 1010651 (2022) - [c7]Harsh Sharma, Nicholas Galioto, Alex A. Gorodetsky, Boris Kramer:
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models. CDC 2022: 6742-6749 - [i16]Harsh Sharma, Boris Kramer:
Preserving Lagrangian structure in data-driven reduced-order modeling of large-scale mechanical systems. CoRR abs/2203.06361 (2022) - [i15]Dongjin Lee, Boris Kramer:
Bi-fidelity conditional-value-at-risk estimation by dimensionally decomposed generalized polynomial chaos expansion. CoRR abs/2204.03133 (2022) - [i14]Harsh Sharma, Nicholas Galioto, Alex A. Gorodetsky, Boris Kramer:
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models. CoRR abs/2209.07646 (2022) - [i13]Dongjin Lee, Boris Kramer:
Multifidelity conditional value-at-risk estimation by dimensionally decomposed generalized polynomial chaos-Kriging. CoRR abs/2212.02728 (2022) - 2021
- [j11]Yizhe Huang, Boris Kramer:
Balanced Reduced-Order Models for Iterative Nonlinear Control of Large-Scale Systems. IEEE Control. Syst. Lett. 5(5): 1699-1704 (2021) - [j10]Boris Kramer:
Stability Domains for Quadratic-Bilinear Reduced-Order Models. SIAM J. Appl. Dyn. Syst. 20(2): 981-996 (2021) - [c6]Yizhe Huang, Boris Kramer:
Balanced Reduced-Order Models for Iterative Nonlinear Control of Large-Scale Systems. ACC 2021: 2788-2793 - [i12]Anirban Chaudhuri, Boris Kramer, Matthew Norton, Johannes O. Royset, Karen Willcox:
Certifiable Risk-Based Engineering Design Optimization. CoRR abs/2101.05129 (2021) - [i11]Nihar Sawant, Boris Kramer, Benjamin Peherstorfer:
Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference. CoRR abs/2107.02597 (2021) - [i10]Harsh Sharma, Zhu Wang, Boris Kramer:
Hamiltonian Operator Inference: Physics-preserving Learning of Reduced-order Models for Hamiltonian Systems. CoRR abs/2107.12996 (2021) - 2020
- [j9]Matthias Heinkenschloss, Boris Kramer, Timur Takhtaganov:
Adaptive Reduced-Order Model Construction for Conditional Value-at-Risk Estimation. SIAM/ASA J. Uncertain. Quantification 8(2): 668-692 (2020) - [j8]Anirban Chaudhuri, Boris Kramer, Karen E. Willcox:
Information Reuse for Importance Sampling in Reliability-Based Design Optimization. Reliab. Eng. Syst. Saf. 201: 106853 (2020) - [i9]Peter Benner, Pawan Goyal, Boris Kramer, Benjamin Peherstorfer, Karen Willcox:
Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms. CoRR abs/2002.09726 (2020) - [i8]Yizhe Huang, Boris Kramer:
Balanced Reduced-Order Models for Iterative Nonlinear Control of Large-Scale Systems. CoRR abs/2012.02305 (2020)
2010 – 2019
- 2019
- [j7]Boris Kramer, Alexandre Noll Marques, Benjamin Peherstorfer, Umberto Villa, Karen Willcox:
Multifidelity probability estimation via fusion of estimators. J. Comput. Phys. 392: 385-402 (2019) - [i7]Boris Kramer, Alexandre Noll Marques, Benjamin Peherstorfer, Umberto Villa, Karen Willcox:
Multifidelity probability estimation via fusion of estimators. CoRR abs/1905.02679 (2019) - [i6]Boris Kramer, Karen E. Willcox:
Balanced Truncation Model Reduction for Lifted Nonlinear Systems. CoRR abs/1907.12084 (2019) - [i5]Renee Swischuk, Boris Kramer, Cheng Huang, Karen Willcox:
Learning physics-based reduced-order models for a single-injector combustion process. CoRR abs/1908.03620 (2019) - [i4]Elizabeth Qian, Boris Kramer, Benjamin Peherstorfer, Karen Willcox:
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems. CoRR abs/1912.08177 (2019) - 2018
- [j6]Benjamin Peherstorfer, Boris Kramer, Karen Willcox:
Multifidelity Preconditioning of the Cross-Entropy Method for Rare Event Simulation and Failure Probability Estimation. SIAM/ASA J. Uncertain. Quantification 6(2): 737-761 (2018) - [j5]Matthias Heinkenschloss, Boris Kramer, Timur Takhtaganov, Karen Willcox:
Conditional-Value-at-Risk Estimation via Reduced-Order Models. SIAM/ASA J. Uncertain. Quantification 6(4): 1395-1423 (2018) - [j4]Boris Kramer, Alex A. Gorodetsky:
System Identification via CUR-Factored Hankel Approximation. SIAM J. Sci. Comput. 40(2) (2018) - [i3]Boris Kramer, Karen Willcox:
Nonlinear Model Order Reduction via Lifting Transformations and Proper Orthogonal Decomposition. CoRR abs/1808.02086 (2018) - 2017
- [j3]Benjamin Peherstorfer, Boris Kramer, Karen Willcox:
Combining multiple surrogate models to accelerate failure probability estimation with expensive high-fidelity models. J. Comput. Phys. 341: 61-75 (2017) - [j2]Boris Kramer, Piyush Grover, Petros Boufounos, Saleh Nabi, Mouhacine Benosman:
Sparse Sensing and DMD-Based Identification of Flow Regimes and Bifurcations in Complex Flows. SIAM J. Appl. Dyn. Syst. 16(2): 1164-1196 (2017) - [j1]Boris Kramer, Benjamin Peherstorfer, Karen Willcox:
Feedback Control for Systems with Uncertain Parameters Using Online-Adaptive Reduced Models. SIAM J. Appl. Dyn. Syst. 16(3): 1563-1586 (2017) - [c5]Mouhacine Benosman, Jeff Borggaard, Boris Kramer:
Robust POD model stabilization for the 3D Boussinesq equations based on Lyapunov theory and extremum seeking. ACC 2017: 1827-1832 - 2016
- [c4]Mouhacine Benosman, Boris Kramer, Petros T. Boufounos, Piyush Grover:
Learning-based reduced order model stabilization for partial differential equations: Application to the coupled Burgers' equation. ACC 2016: 1673-1678 - [c3]Boris Kramer:
Model reduction for control of a multiphysics system: Coupled Burgers' equation. ACC 2016: 6146-6151 - [i2]Mouhacine Benosman, Jeff Borggaard, Boris Kramer:
Robust Reduced-Order Model Stabilization for Partial Differential Equations Based on Lyapunov Theory and Extremum Seeking with Application to the 3D Boussinesq Equations. CoRR abs/1604.04586 (2016) - 2015
- [c2]John A. Burns, Boris Kramer:
Full flux models for optimization and control of heat exchangers. ACC 2015: 577-582 - [i1]Mouhacine Benosman, Boris Kramer, Petros Boufounos, Piyush Grover:
Learning-based Reduced Order Model Stabilization for Partial Differential Equations: Application to the Coupled Burgers Equation. CoRR abs/1510.01728 (2015) - 2012
- [c1]Alex Zwanenburg, Eduard Meijer, Ward Jennekens, Carola van Pul, Boris Kramer, Peter Andriessen:
Automatic detection of burst synchrony in preterm infants. EMBC 2012: 4720-4723
Coauthor Index
aka: Karen E. Willcox
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last updated on 2024-09-22 23:34 CEST by the dblp team
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