Leveraging time and parameters for nonlinear model reduction methods
Fuente:
arXiv
Saved in:
| Main Authors: | Glas, Silke, Unger, Benjamin |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Structure-preserving model reduction on manifolds of port-Hamiltonian systems
by: Glas, Silke, et al.
Published: (2026)
by: Glas, Silke, et al.
Published: (2026)
Nonlinear model reduction for transport-dominated problems
by: Hesthaven, Jan S., et al.
Published: (2026)
by: Hesthaven, Jan S., et al.
Published: (2026)
Certified machine learning: A posteriori error estimation for physics-informed neural networks
by: Hillebrecht, Birgit, et al.
Published: (2022)
by: Hillebrecht, Birgit, et al.
Published: (2022)
Certified machine learning: Rigorous a posteriori error bounds for PDE defined PINNs
by: Hillebrecht, Birgit, et al.
Published: (2022)
by: Hillebrecht, Birgit, et al.
Published: (2022)
Model reduction on manifolds: A differential geometric framework
by: Buchfink, Patrick, et al.
Published: (2023)
by: Buchfink, Patrick, et al.
Published: (2023)
Neural active manifolds: nonlinear dimensionality reduction for uncertainty quantification
by: Zanoni, Andrea, et al.
Published: (2024)
by: Zanoni, Andrea, et al.
Published: (2024)
Sequential-in-time training of nonlinear parametrizations for solving time-dependent partial differential equations
by: Zhang, Huan, et al.
Published: (2024)
by: Zhang, Huan, et al.
Published: (2024)
Filtered Neural Galerkin model reduction schemes for efficient propagation of initial condition uncertainties in digital twins
by: Ning, Zhiyang, et al.
Published: (2025)
by: Ning, Zhiyang, et al.
Published: (2025)
Parametric model reduction of mean-field and stochastic systems via higher-order action matching
by: Berman, Jules, et al.
Published: (2024)
by: Berman, Jules, et al.
Published: (2024)
Model order reduction via Lie groups
by: Wotte, Yannik P., et al.
Published: (2025)
by: Wotte, Yannik P., et al.
Published: (2025)
A local approach to parameter space reduction for regression and classification tasks
by: Romor, Francesco, et al.
Published: (2021)
by: Romor, Francesco, et al.
Published: (2021)
Latent Dynamics Graph Convolutional Networks for model order reduction of parameterized time-dependent PDEs
by: Tomada, Lorenzo, et al.
Published: (2026)
by: Tomada, Lorenzo, et al.
Published: (2026)
Nonlinear model reduction for operator learning
by: Eivazi, Hamidreza, et al.
Published: (2024)
by: Eivazi, Hamidreza, et al.
Published: (2024)
Energy-stable Port-Hamiltonian Systems
by: Buchfink, Patrick, et al.
Published: (2025)
by: Buchfink, Patrick, et al.
Published: (2025)
TGPT-PINN: Nonlinear model reduction with transformed GPT-PINNs
by: Chen, Yanlai, et al.
Published: (2024)
by: Chen, Yanlai, et al.
Published: (2024)
Nonlinear energy-preserving model reduction with lifting transformations that quadratize the energy
by: Sharma, Harsh, et al.
Published: (2025)
by: Sharma, Harsh, et al.
Published: (2025)
On latent dynamics learning in nonlinear reduced order modeling
by: Farenga, Nicola, et al.
Published: (2024)
by: Farenga, Nicola, et al.
Published: (2024)
A fast neural hybrid Newton solver adapted to implicit methods for nonlinear dynamics
by: Jin, Tianyu, et al.
Published: (2024)
by: Jin, Tianyu, et al.
Published: (2024)
A Dirac-Frenkel-Onsager principle: Instantaneous residual minimization with gauge momentum for nonlinear parametrizations of PDE solutions
by: Raviola, Matteo, et al.
Published: (2026)
by: Raviola, Matteo, et al.
Published: (2026)
Enabling stratified sampling in high dimensions via nonlinear dimensionality reduction
by: Geraci, Gianluca, et al.
Published: (2025)
by: Geraci, Gianluca, et al.
Published: (2025)
Stein's method for marginals on large graphical models
by: Cui, Tiangang, et al.
Published: (2024)
by: Cui, Tiangang, et al.
Published: (2024)
A nonlinear extension of parametric model embedding for dimensionality reduction in parametric shape design
by: Serani, Andrea, et al.
Published: (2026)
by: Serani, Andrea, et al.
Published: (2026)
How to reveal the rank of a matrix?
by: Damle, Anil, et al.
Published: (2024)
by: Damle, Anil, et al.
Published: (2024)
Handling geometrical variability in nonlinear reduced order modeling through Continuous Geometry-Aware DL-ROMs
by: Brivio, Simone, et al.
Published: (2024)
by: Brivio, Simone, et al.
Published: (2024)
Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation
by: Ivagnes, Anna, et al.
Published: (2022)
by: Ivagnes, Anna, et al.
Published: (2022)
Stochastic generative methods for stable and accurate closure modeling of chaotic dynamical systems
by: Williams, Emily, et al.
Published: (2025)
by: Williams, Emily, et al.
Published: (2025)
CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
by: Berman, Jules, et al.
Published: (2024)
by: Berman, Jules, et al.
Published: (2024)
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs
by: Brivio, Simone, et al.
Published: (2024)
by: Brivio, Simone, et al.
Published: (2024)
Dimension reduction for derivative-informed operator learning: An analysis of approximation errors
by: Luo, Dingcheng, et al.
Published: (2025)
by: Luo, Dingcheng, et al.
Published: (2025)
Probabilistic operator learning: generative modeling and uncertainty quantification for foundation models of differential equations
by: Zhang, Benjamin J., et al.
Published: (2025)
by: Zhang, Benjamin J., et al.
Published: (2025)
Leveraging Gauge Freedom for Learning Non-Gradient Population Dynamics of Stochastic Systems
by: Berman, Jules, et al.
Published: (2026)
by: Berman, Jules, et al.
Published: (2026)
Estimation of instrument and noise parameters for inverse problem based on prior diffusion model
by: Giovannelli, Jean-François
Published: (2026)
by: Giovannelli, Jean-François
Published: (2026)
Stochastic diagonal estimation with adaptive parameter selection
by: Han, Zongyuan, et al.
Published: (2024)
by: Han, Zongyuan, et al.
Published: (2024)
Leveraging Real-Time Data Analysis and Multiple Kernel Learning for Manufacturing of Innovative Steels
by: Rannetbauer, Wolfgang, et al.
Published: (2025)
by: Rannetbauer, Wolfgang, et al.
Published: (2025)
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling
by: Chatalic, Antoine, et al.
Published: (2023)
by: Chatalic, Antoine, et al.
Published: (2023)
A model-data asymptotic-preserving neural network method based on micro-macro decomposition for gray radiative transfer equations
by: Li, Hongyan, et al.
Published: (2022)
by: Li, Hongyan, et al.
Published: (2022)
Flow-based Bayesian filtering for high-dimensional nonlinear stochastic dynamical systems
by: Wang, Xintong, et al.
Published: (2025)
by: Wang, Xintong, et al.
Published: (2025)
DPG loss functions for learning parameter-to-solution maps by neural networks
by: Castillo, Pablo Cortés, et al.
Published: (2025)
by: Castillo, Pablo Cortés, et al.
Published: (2025)
Diffeomorphism Neural Operator for various domains and parameters of partial differential equations
by: Zhao, Zhiwei, et al.
Published: (2024)
by: Zhao, Zhiwei, et al.
Published: (2024)
A Generative Sampler for distributions with possible discrete parameter based on Reversibility
by: Li, Lei, et al.
Published: (2026)
by: Li, Lei, et al.
Published: (2026)
Similar Items
-
Structure-preserving model reduction on manifolds of port-Hamiltonian systems
by: Glas, Silke, et al.
Published: (2026) -
Nonlinear model reduction for transport-dominated problems
by: Hesthaven, Jan S., et al.
Published: (2026) -
Certified machine learning: A posteriori error estimation for physics-informed neural networks
by: Hillebrecht, Birgit, et al.
Published: (2022) -
Certified machine learning: Rigorous a posteriori error bounds for PDE defined PINNs
by: Hillebrecht, Birgit, et al.
Published: (2022) -
Model reduction on manifolds: A differential geometric framework
by: Buchfink, Patrick, et al.
Published: (2023)