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Boris Kramer

Data-driven Model Reduction for Soft Robots via Lagrangian Operator Inference

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Jul 11, 2024
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Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling

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Jan 23, 2024
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Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds

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May 24, 2023
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Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models

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Sep 15, 2022
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Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference

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Jul 06, 2021
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Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms

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Feb 22, 2020
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Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems

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Feb 07, 2020
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Learning physics-based reduced-order models for a single-injector combustion process

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Aug 13, 2019
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