Saved in:
| Main Author: | Szalai, Robert |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.14514 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Non-resonant invariant foliations of quasi-periodically forced systems
by: Szalai, Robert
Published: (2024)
by: Szalai, Robert
Published: (2024)
Data-driven modelling of autonomous and forced dynamical systems
by: Szalai, Robert
Published: (2025)
by: Szalai, Robert
Published: (2025)
Higher order quantum reservoir computing for non-intrusive reduced-order models
by: Jain, Vinamr, et al.
Published: (2024)
by: Jain, Vinamr, et al.
Published: (2024)
One-shot learning for the complex dynamical behaviors of weakly nonlinear forced oscillators
by: Ma, Teng, et al.
Published: (2026)
by: Ma, Teng, et al.
Published: (2026)
Deep learning for model correction of dynamical systems with data scarcity
by: Tatsuoka, Caroline, et al.
Published: (2024)
by: Tatsuoka, Caroline, et al.
Published: (2024)
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling
by: Galioto, Nicholas, et al.
Published: (2024)
by: Galioto, Nicholas, et al.
Published: (2024)
Data-driven forced response analysis with min-max representations of nonlinear restoring forces
by: Saito, Akira, et al.
Published: (2026)
by: Saito, Akira, et al.
Published: (2026)
How iteration order influences convergence and stability in deep learning
by: Dherin, Benoit, et al.
Published: (2025)
by: Dherin, Benoit, et al.
Published: (2025)
Let's do the time-warp-attend: Learning topological invariants of dynamical systems
by: Moriel, Noa, et al.
Published: (2023)
by: Moriel, Noa, et al.
Published: (2023)
Machine learning identifies nullclines in oscillatory dynamical systems
by: Prokop, Bartosz, et al.
Published: (2025)
by: Prokop, Bartosz, et al.
Published: (2025)
Physics-guided weak-form discovery of reduced-order models for trapped ultracold hydrodynamics
by: Wang, Reuben R. W., et al.
Published: (2024)
by: Wang, Reuben R. W., et al.
Published: (2024)
VENI, VINDy, VICI: a generative reduced-order modeling framework with uncertainty quantification
by: Conti, Paolo, et al.
Published: (2024)
by: Conti, Paolo, et al.
Published: (2024)
Data-driven model order reduction for structures with piecewise linear nonlinearity using dynamic mode decomposition
by: Saito, Akira, et al.
Published: (2026)
by: Saito, Akira, et al.
Published: (2026)
Deficiency of equation-finding approach to data-driven modeling of dynamical systems
by: Zhai, Zheng-Meng, et al.
Published: (2025)
by: Zhai, Zheng-Meng, et al.
Published: (2025)
Training neural operators to preserve invariant measures of chaotic attractors
by: Jiang, Ruoxi, et al.
Published: (2023)
by: Jiang, Ruoxi, et al.
Published: (2023)
Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection
by: Plotzki, Tim, et al.
Published: (2026)
by: Plotzki, Tim, et al.
Published: (2026)
Machine Learning for the identification of phase-transitions in interacting agent-based systems: a Desai-Zwanzig example
by: Evangelou, Nikolaos, et al.
Published: (2023)
by: Evangelou, Nikolaos, et al.
Published: (2023)
Machine-Precision Prediction of Low-Dimensional Chaotic Systems
by: Schötz, Christof, et al.
Published: (2025)
by: Schötz, Christof, et al.
Published: (2025)
Dictionary learning for Kernel EDMD
by: Bolager, Erik Lien, et al.
Published: (2026)
by: Bolager, Erik Lien, et al.
Published: (2026)
Deep learning and the rate of approximation by flows
by: Cheng, Jingpu, et al.
Published: (2026)
by: Cheng, Jingpu, et al.
Published: (2026)
Improved deep learning of chaotic dynamical systems with multistep penalty losses
by: Chakraborty, Dibyajyoti, et al.
Published: (2024)
by: Chakraborty, Dibyajyoti, et al.
Published: (2024)
Noise-induced degeneration in online learning
by: Sato, Yuzuru, et al.
Published: (2020)
by: Sato, Yuzuru, et al.
Published: (2020)
Deep learning for predicting the occurrence of tipping points
by: Zhuge, Chengzuo, et al.
Published: (2024)
by: Zhuge, Chengzuo, et al.
Published: (2024)
On using Machine Learning Algorithms for Motorcycle Collision Detection
by: Rodegast, Philipp, et al.
Published: (2024)
by: Rodegast, Philipp, et al.
Published: (2024)
Probabilistic function-on-function nonlinear autoregressive model for emulation and reliability analysis of dynamical systems
by: Song, Zhouzhou, et al.
Published: (2026)
by: Song, Zhouzhou, et al.
Published: (2026)
Birkhoff sections in 3-manifold with invariant toric foliation
by: Kuang, Wentian
Published: (2025)
by: Kuang, Wentian
Published: (2025)
Hierarchical deep learning-based adaptive time-stepping scheme for multiscale simulations
by: Hamid, Asif, et al.
Published: (2023)
by: Hamid, Asif, et al.
Published: (2023)
How deep is your network? Deep vs. shallow learning of transfer operators
by: Tabish, Mohammad, et al.
Published: (2025)
by: Tabish, Mohammad, et al.
Published: (2025)
Control of dynamical systems with neural networks
by: Böttcher, Lucas
Published: (2025)
by: Böttcher, Lucas
Published: (2025)
Hierarchy of extreme-event predictability in turbulence revealed by machine learning
by: Yang, Yuxuan, et al.
Published: (2026)
by: Yang, Yuxuan, et al.
Published: (2026)
Enhancing generalizability of model discovery across parameter space with multi-experiment equation learning (ME-EQL)
by: Ciocanel, Maria-Veronica, et al.
Published: (2025)
by: Ciocanel, Maria-Veronica, et al.
Published: (2025)
Dynamical systems and complex networks: A Koopman operator perspective
by: Klus, Stefan, et al.
Published: (2024)
by: Klus, Stefan, et al.
Published: (2024)
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements
by: Ma, Mason, et al.
Published: (2023)
by: Ma, Mason, et al.
Published: (2023)
Reservoir computing for system identification and predictive control with limited data
by: Williams, Jan P., et al.
Published: (2024)
by: Williams, Jan P., et al.
Published: (2024)
Learning dynamical systems from data: Gradient-based dictionary optimization
by: Tabish, Mohammad, et al.
Published: (2024)
by: Tabish, Mohammad, et al.
Published: (2024)
Data-driven system identification using quadratic embeddings of nonlinear dynamics
by: Klus, Stefan, et al.
Published: (2025)
by: Klus, Stefan, et al.
Published: (2025)
Navigating Uncertainties in Machine Learning for Structural Dynamics: A Comprehensive Survey of Probabilistic and Non-Probabilistic Approaches in Forward and Inverse Problems
by: Yan, Wang-Ji, et al.
Published: (2024)
by: Yan, Wang-Ji, et al.
Published: (2024)
On the Stability of a non-hyperbolic nonlinear map with non-bounded set of non-isolated fixed points with applications to Machine Learning
by: Hansen, Roberta, et al.
Published: (2024)
by: Hansen, Roberta, et al.
Published: (2024)
Explicit construction of recurrent neural networks effectively approximating discrete dynamical systems
by: Nakayama, Chikara, et al.
Published: (2024)
by: Nakayama, Chikara, et al.
Published: (2024)
A scalable generative model for dynamical system reconstruction from neuroimaging data
by: Volkmann, Eric, et al.
Published: (2024)
by: Volkmann, Eric, et al.
Published: (2024)
Similar Items
-
Non-resonant invariant foliations of quasi-periodically forced systems
by: Szalai, Robert
Published: (2024) -
Data-driven modelling of autonomous and forced dynamical systems
by: Szalai, Robert
Published: (2025) -
Higher order quantum reservoir computing for non-intrusive reduced-order models
by: Jain, Vinamr, et al.
Published: (2024) -
One-shot learning for the complex dynamical behaviors of weakly nonlinear forced oscillators
by: Ma, Teng, et al.
Published: (2026) -
Deep learning for model correction of dynamical systems with data scarcity
by: Tatsuoka, Caroline, et al.
Published: (2024)