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05/24/2023
Reversible and irreversible bracket-based dynamics for deep graph neural networks
Recent works have shown that physics-inspired architectures allow the tr...
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04/13/2023
Canonical and Noncanonical Hamiltonian Operator Inference
A method for the nonintrusive and structure-preserving model reduction o...
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06/15/2022
A Multifidelity Monte Carlo Method for Realistic Computational Budgets
A method for the multifidelity Monte Carlo (MFMC) estimation of statisti...
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04/17/2022
Energetically Consistent Model Reduction for Metriplectic Systems
The metriplectic formalism is useful for describing complete dynamical s...
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12/02/2021
Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation
Due to the curse of dimensionality and the limitation on training data, ...
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10/05/2021
A Comparison of Neural Network Architectures for Data-Driven Reduced-Order Modeling
The popularity of deep convolutional autoencoders (CAEs) has engendered ...
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04/29/2021
Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations
A dimension reduction method based on the "Nonlinear Level set Learning"...
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07/22/2019