Copertina

Fast-Slow Neural Networks for Learning Singularly Perturbed Dynamical Systems

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Serino, Daniel A., Loya, Allen Alvarez, Burby, Joshua W., Kevrekidis, Ioannis G., Tang, Qi
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Dynamical Systems Computational Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Robust computation of higher-dimensional invariant tori from individual trajectories
di: Ruth, Maximilian, et al.
Pubblicazione: (2025)

Structure-Preserving Neural Ordinary Differential Equations for Stiff Systems
di: Loya, Allen Alvarez, et al.
Pubblicazione: (2025)

Machine Learning for the identification of phase-transitions in interacting agent-based systems: a Desai-Zwanzig example
di: Evangelou, Nikolaos, et al.
Pubblicazione: (2023)

Fast and Flexible Probabilistic Forecasting of Dynamical Systems using Flow Matching and Physical Perturbation
di: Rout, Siddharth, et al.
Pubblicazione: (2025)

On the Dynamics of Complex Quadratic Families under Holomorphic and Non-Holomorphic Singular Perturbations
di: Shang, Haitao
Pubblicazione: (2020)

Latent Space Dynamics Learning for Stiff Collisional-radiative Models
di: Xie, Xuping, et al.
Pubblicazione: (2024)

Conformal Disentanglement: A Neural Framework for Perspective Synthesis and Differentiation
di: Kevrekidis, George A., et al.
Pubblicazione: (2024)

MPINeuralODE: Multiple-Initial-Condition Physics-Informed Neural ODEs for Globally Consistent Dynamical System Learning
di: Yang, Lake, et al.
Pubblicazione: (2026)

Neural Network Representations of Multiphase Equations of State
di: Kevrekidis, George A., et al.
Pubblicazione: (2024)

Generative Learning for Slow Manifolds and Bifurcation Diagrams
di: Crabtree, Ellis R., et al.
Pubblicazione: (2025)

Fast Reactions and Slow Manifolds
di: Kuehn, Christian, et al.
Pubblicazione: (2023)

Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning
di: Patsatzis, Dimitrios G., et al.
Pubblicazione: (2023)

Reduced models in chemical kinetics via nonlinear data-mining
di: Chiavazzo, Eliodoro, et al.
Pubblicazione: (2013)

Nonlinear Diffusion on Networks: Perturbations and Consensus Dynamics
di: Bonetto, Riccardo, et al.
Pubblicazione: (2022)

Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification
di: Giovanis, Dimitris G., et al.
Pubblicazione: (2024)

Reduced Order Modeling of Nonlinear Dynamical Systems Using Slow Manifolds
di: Wilson, Dan
Pubblicazione: (2025)

Dynamically Optimal Projection onto Slow Spectral Manifolds for Linear Systems
di: Kogelbauer, Florian, et al.
Pubblicazione: (2025)

Neural Ordinary Differential Equations for Learning and Extrapolating System Dynamics Across Bifurcations
di: van Tegelen, Eva, et al.
Pubblicazione: (2025)

Infinite dimensional Slow Manifolds for a Linear Fast-Reaction System
di: Kuehn, Christian, et al.
Pubblicazione: (2024)

$α$-SGHN: A Robust Model for Learning Particle Interactions in Lattice Systems
di: Gao, Yixian, et al.
Pubblicazione: (2024)

Constructing Linear Operators Using Classical Perturbation Theory
di: Avillez, Miguel, et al.
Pubblicazione: (2024)

Online learning of Koopman operator using streaming data from different dynamical regimes
di: Loya, Kartik, et al.
Pubblicazione: (2024)

Koopman Operator Framework for Modeling and Control of Off-Road Vehicle on Deformable Terrain
di: Loya, Kartik, et al.
Pubblicazione: (2026)

Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks
di: Alvarez, Hector Vargas, et al.
Pubblicazione: (2024)

Local Universal Splitting Integrators for Contact Hamiltonian Systems
di: Kevrekidis, George A
Pubblicazione: (2026)

Information Criteria Fail for Dynamical Systems: Sampling Rate and Dimension Dependence
di: Utkarsh, Kumar, et al.
Pubblicazione: (2025)

Identifying Equivalent Training Dynamics
di: Redman, William T., et al.
Pubblicazione: (2023)

Dictionary learning for Kernel EDMD
di: Bolager, Erik Lien, et al.
Pubblicazione: (2026)

Learning Generalized Diffusions using an Energetic Variational Approach
di: Lu, Yubin, et al.
Pubblicazione: (2024)

Identification and Computation of Slow Manifolds Using the Isostable Coordinate System
di: Wilson, Dan
Pubblicazione: (2025)

Thermodynamic Formalism and Perturbation Formulae for Quenched Random Open Dynamical Systems
di: Atnip, Jason, et al.
Pubblicazione: (2023)

Symmetry Groups of Basins of Attraction in Equivariant Dynamical Systems
di: Xie, Xiao
Pubblicazione: (2025)

Neural Context Flows for Meta-Learning of Dynamical Systems
di: Nzoyem, Roussel Desmond, et al.
Pubblicazione: (2024)

Streams, Graphs and Global Attractors of Dynamical Systems on Locally Compact Spaces
di: De Leo, Roberto, et al.
Pubblicazione: (2025)

On Learning what to Learn: heterogeneous observations of dynamics and establishing (possibly causal) relations among them
di: Sroczynski, David W., et al.
Pubblicazione: (2024)

Steady State Classification of Allee Effect System
di: Song, Kuo, et al.
Pubblicazione: (2025)

Iterative Learning Control of Fast, Nonlinear, Oscillatory Dynamics (Preprint)
di: Brooks, John W., et al.
Pubblicazione: (2024)

A Generalization for Ultradiscrete Limit Cycles in a Certain Type of Max-Plus Dynamical Systems
di: Ohmori, Shousuke, et al.
Pubblicazione: (2024)

On the Equivalence of Equilibrium and Freezing States in Dynamical Systems
di: Hedges, C. Evans
Pubblicazione: (2024)

Structure-Preserving Learning of Nonholonomic Dynamics
di: Beckers, Thomas, et al.
Pubblicazione: (2026)