Principal Component Flow Map Learning of PDEs from Incomplete, Limited, and Noisy Data
Fuente:
arXiv
Guardado en:
| Autor principal: | Churchill, Victor |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Traffic Flow Reconstruction from Limited Collected Data
por: Baloul, Nail, et al.
Publicado: (2026)
por: Baloul, Nail, et al.
Publicado: (2026)
A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series
por: Li, Xuyang, et al.
Publicado: (2025)
por: Li, Xuyang, et al.
Publicado: (2025)
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements
por: Ma, Mason, et al.
Publicado: (2023)
por: Ma, Mason, et al.
Publicado: (2023)
Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification
por: Giovanis, Dimitris G., et al.
Publicado: (2024)
por: Giovanis, Dimitris G., et al.
Publicado: (2024)
Neural Context Flows for Meta-Learning of Dynamical Systems
por: Nzoyem, Roussel Desmond, et al.
Publicado: (2024)
por: Nzoyem, Roussel Desmond, et al.
Publicado: (2024)
Data-Assimilated Model-Based Reinforcement Learning for Partially Observed Chaotic Flows
por: Ozan, Defne E., et al.
Publicado: (2025)
por: Ozan, Defne E., et al.
Publicado: (2025)
ParallelFlow: Parallelizing Linear Transformers via Flow Discretization
por: Cirone, Nicola Muca, et al.
Publicado: (2025)
por: Cirone, Nicola Muca, et al.
Publicado: (2025)
Autoencoding Dynamics: Topological Limitations and Capabilities
por: Kvalheim, Matthew D., et al.
Publicado: (2025)
por: Kvalheim, Matthew D., et al.
Publicado: (2025)
Adaptive Kernel Selection for Kernelized Diffusion Maps
por: Aboussaad, Othmane, et al.
Publicado: (2026)
por: Aboussaad, Othmane, et al.
Publicado: (2026)
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing Flows and the Feynman-Kac Formula
por: Bekri, Naoufal El, et al.
Publicado: (2025)
por: Bekri, Naoufal El, et al.
Publicado: (2025)
On the Unique Recovery of Transport Maps and Vector Fields from Finite Measure-Valued Data
por: Botvinick-Greenhouse, Jonah, et al.
Publicado: (2026)
por: Botvinick-Greenhouse, Jonah, et al.
Publicado: (2026)
Enhancing Solutions for Complex PDEs: Introducing Complementary Convolution and Equivariant Attention in Fourier Neural Operators
por: Zhao, Xuanle, et al.
Publicado: (2023)
por: Zhao, Xuanle, et al.
Publicado: (2023)
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data Assimilation
por: Chen, Chuanqi, et al.
Publicado: (2024)
por: Chen, Chuanqi, et al.
Publicado: (2024)
Flowing Through Layers: A Continuous Dynamical Systems Perspective on Transformers
por: Fein-Ashley, Jacob
Publicado: (2025)
por: Fein-Ashley, Jacob
Publicado: (2025)
Flow map matching with stochastic interpolants: A mathematical framework for consistency models
por: Boffi, Nicholas M., et al.
Publicado: (2024)
por: Boffi, Nicholas M., et al.
Publicado: (2024)
Absence of Closed-Form Descriptions for Gradient Flow in Two-Layer Narrow Networks
por: Park, Yeachan
Publicado: (2024)
por: Park, Yeachan
Publicado: (2024)
Gradient Flow Equations for Deep Linear Neural Networks: A Survey from a Network Perspective
por: Wendin, Joel, et al.
Publicado: (2025)
por: Wendin, Joel, et al.
Publicado: (2025)
CP-PINNs: Data-Driven Changepoints Detection in PDEs Using Online Optimized Physics-Informed Neural Networks
por: Dong, Zhikang, et al.
Publicado: (2022)
por: Dong, Zhikang, et al.
Publicado: (2022)
Weighted Birkhoff Averages Accelerate Data-Driven Methods
por: Bou-Sakr-El-Tayar, Maria, et al.
Publicado: (2025)
por: Bou-Sakr-El-Tayar, Maria, et al.
Publicado: (2025)
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
por: Brenner, Manuel, et al.
Publicado: (2022)
por: Brenner, Manuel, et al.
Publicado: (2022)
Variational Mode Decomposition-Based Nonstationary Coherent Structure Analysis for Spatiotemporal Data
por: Ohmichi, Yuya
Publicado: (2023)
por: Ohmichi, Yuya
Publicado: (2023)
Data-driven forced response analysis with min-max representations of nonlinear restoring forces
por: Saito, Akira, et al.
Publicado: (2026)
por: Saito, Akira, et al.
Publicado: (2026)
Learning Collective Behaviors from Observation
por: Feng, Jinchao, et al.
Publicado: (2023)
por: Feng, Jinchao, et al.
Publicado: (2023)
Data-driven model order reduction for structures with piecewise linear nonlinearity using dynamic mode decomposition
por: Saito, Akira, et al.
Publicado: (2026)
por: Saito, Akira, et al.
Publicado: (2026)
Learning dynamical systems from data: Gradient-based dictionary optimization
por: Tabish, Mohammad, et al.
Publicado: (2024)
por: Tabish, Mohammad, et al.
Publicado: (2024)
Dynamics-Informed Deep Learning for Predicting Extreme Events
por: Katsidoniotaki, Eirini, et al.
Publicado: (2026)
por: Katsidoniotaki, Eirini, et al.
Publicado: (2026)
MXMap: A Multivariate Cross Mapping Framework for Causal Discovery in Dynamical Systems
por: Zhang, Elise, et al.
Publicado: (2025)
por: Zhang, Elise, et al.
Publicado: (2025)
Learning From Simulators: A Theory of Simulation-Grounded Learning
por: Dudley, Carson, et al.
Publicado: (2025)
por: Dudley, Carson, et al.
Publicado: (2025)
Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach
por: Lengyel, Daniel, et al.
Publicado: (2024)
por: Lengyel, Daniel, et al.
Publicado: (2024)
Optimal Initialization in Depth: Lyapunov Initialization and Limit Theorems for Deep Leaky ReLU Networks
por: Kogler, Constantin, et al.
Publicado: (2026)
por: Kogler, Constantin, et al.
Publicado: (2026)
Data-driven system identification using quadratic embeddings of nonlinear dynamics
por: Klus, Stefan, et al.
Publicado: (2025)
por: Klus, Stefan, et al.
Publicado: (2025)
Adaptive control of reaction-diffusion PDEs via neural operator-approximated gain kernels
por: Bhan, Luke, et al.
Publicado: (2024)
por: Bhan, Luke, et al.
Publicado: (2024)
Deep Learning of the Evolution Operator Enables Forecasting of Out-of-Training Dynamics in Chaotic Systems
por: Shokar, Ira J. S., et al.
Publicado: (2025)
por: Shokar, Ira J. S., et al.
Publicado: (2025)
Data-Specific Hyper-Parameter Design: A Paradigm Shift in Reservoir Computing
por: Manjunath, G, et al.
Publicado: (2026)
por: Manjunath, G, et al.
Publicado: (2026)
Learning the Simplest Neural ODE
por: Okamoto, Yuji, et al.
Publicado: (2025)
por: Okamoto, Yuji, et al.
Publicado: (2025)
Koopman Learning with Episodic Memory
por: Redman, William T., et al.
Publicado: (2023)
por: Redman, William T., et al.
Publicado: (2023)
Multitask Learning with Stochastic Interpolants
por: Negrel, Hugo, et al.
Publicado: (2025)
por: Negrel, Hugo, et al.
Publicado: (2025)
On the Limitations of Fractal Dimension as a Measure of Generalization
por: Tan, Charlie B., et al.
Publicado: (2024)
por: Tan, Charlie B., et al.
Publicado: (2024)
On Data-Driven Koopman Representations of Nonlinear Delay Differential Equations
por: Rajkumar, Santosh Mohan, et al.
Publicado: (2026)
por: Rajkumar, Santosh Mohan, et al.
Publicado: (2026)
Data-efficient Kernel Methods for Learning Hamiltonian Systems
por: Jalalian, Yasamin, et al.
Publicado: (2025)
por: Jalalian, Yasamin, et al.
Publicado: (2025)
Ejemplares similares
-
Traffic Flow Reconstruction from Limited Collected Data
por: Baloul, Nail, et al.
Publicado: (2026) -
A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series
por: Li, Xuyang, et al.
Publicado: (2025) -
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements
por: Ma, Mason, et al.
Publicado: (2023) -
Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification
por: Giovanis, Dimitris G., et al.
Publicado: (2024) -
Neural Context Flows for Meta-Learning of Dynamical Systems
por: Nzoyem, Roussel Desmond, et al.
Publicado: (2024)