Saved in:
| Main Authors: | Lin, Bo, Belardinelli, Pierpaolo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.05050 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
Invariant Measures in Time-Delay Coordinates for Unique Dynamical System Identification
by: Botvinick-Greenhouse, Jonah, et al.
Published: (2024)
by: Botvinick-Greenhouse, Jonah, et al.
Published: (2024)
Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing
by: Norton, Declan A., et al.
Published: (2025)
by: Norton, Declan A., et al.
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)
CEBoosting: Online Sparse Identification of Dynamical Systems with Regime Switching by Causation Entropy Boosting
by: Chen, Chuanqi, et al.
Published: (2023)
by: Chen, Chuanqi, et al.
Published: (2023)
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)
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)
State Estimation Using Sparse DEIM and Recurrent Neural Networks
by: Farazmand, Mohammad
Published: (2024)
by: Farazmand, Mohammad
Published: (2024)
Complex fractal trainability boundary can arise from trivial non-convexity
by: Liu, Yizhou
Published: (2024)
by: Liu, Yizhou
Published: (2024)
FEG-Pro: Forecast-Error Growth Profiling for Finite-Horizon Instability Analysis of Nonlinear Time Series
by: Velichko, Andrei, et al.
Published: (2026)
by: Velichko, Andrei, et al.
Published: (2026)
Backpropagation on Dynamical Networks
by: Tan, Eugene, et al.
Published: (2022)
by: Tan, Eugene, et al.
Published: (2022)
Deep Learning of the Evolution Operator Enables Forecasting of Out-of-Training Dynamics in Chaotic Systems
by: Shokar, Ira J. S., et al.
Published: (2025)
by: Shokar, Ira J. S., et al.
Published: (2025)
Dynamics-Informed Deep Learning for Predicting Extreme Events
by: Katsidoniotaki, Eirini, et al.
Published: (2026)
by: Katsidoniotaki, Eirini, et al.
Published: (2026)
Machine-Precision Prediction of Low-Dimensional Chaotic Systems
by: Schötz, Christof, et al.
Published: (2025)
by: Schötz, Christof, et al.
Published: (2025)
PINN-Obs: Physics-Informed Neural Network-Based Observer for Nonlinear Dynamical Systems
by: Farkane, Ayoub, et al.
Published: (2025)
by: Farkane, Ayoub, et al.
Published: (2025)
Weighted Birkhoff Averages Accelerate Data-Driven Methods
by: Bou-Sakr-El-Tayar, Maria, et al.
Published: (2025)
by: Bou-Sakr-El-Tayar, Maria, et al.
Published: (2025)
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
by: Brenner, Manuel, et al.
Published: (2022)
by: Brenner, Manuel, et al.
Published: (2022)
Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming
by: Qu, Yongquan, et al.
Published: (2024)
by: Qu, Yongquan, et al.
Published: (2024)
Conditioning on PDE Parameters to Generalise Deep Learning Emulation of Stochastic and Chaotic Dynamics
by: Shokar, Ira J. S., et al.
Published: (2025)
by: Shokar, Ira J. S., et al.
Published: (2025)
Geometric structure of ideal data-driven dynamical model using RfR method
by: Tsutsumi, Natsuki, et al.
Published: (2026)
by: Tsutsumi, Natsuki, et al.
Published: (2026)
Designing Chaotic Attractors: A Semi-supervised Approach
by: Kabayama, Tempei, et al.
Published: (2024)
by: Kabayama, Tempei, et al.
Published: (2024)
Attractor-merging Crises and Intermittency in Reservoir Computing
by: Kabayama, Tempei, et al.
Published: (2025)
by: Kabayama, Tempei, et al.
Published: (2025)
Generative Lagrangian data assimilation for ocean dynamics under extreme sparsity
by: Asefi, Niloofar, et al.
Published: (2025)
by: Asefi, Niloofar, et al.
Published: (2025)
Chaoticus: a parallel approach to the computation of chaos indicators
by: Jiménez-López, Javier, et al.
Published: (2025)
by: Jiménez-López, Javier, et al.
Published: (2025)
Data-driven model discovery with Kolmogorov-Arnold networks
by: Moradi, Mohammadamin, et al.
Published: (2024)
by: Moradi, Mohammadamin, et al.
Published: (2024)
Data-Driven Reduced-Complexity Modeling of Fluid Flows: A Community Challenge
by: Schmidt, Oliver T., et al.
Published: (2026)
by: Schmidt, Oliver T., et al.
Published: (2026)
Investigating Hamiltonian Dynamics by the Method of Covariant Lyapunov Vectors
by: Plessis, Jean-Jacq du
Published: (2025)
by: Plessis, Jean-Jacq du
Published: (2025)
Fractals in rate-induced tipping
by: Wang, Jason Qianchuan, et al.
Published: (2026)
by: Wang, Jason Qianchuan, et al.
Published: (2026)
Learning finite symmetry groups of dynamical systems via equivariance detection
by: Calvo-Barlés, Pablo, et al.
Published: (2025)
by: Calvo-Barlés, Pablo, et al.
Published: (2025)
Tailored Forecasting from Short Time Series via Meta-learning
by: Norton, Declan A., et al.
Published: (2025)
by: Norton, Declan A., et al.
Published: (2025)
PySHRED: A Python package for SHallow REcurrent Decoding for sparse sensing, model reduction and scientific discovery
by: Ye, David, et al.
Published: (2025)
by: Ye, David, et al.
Published: (2025)
On the Melnikov method for fractional-order systems
by: Li, Hang, et al.
Published: (2024)
by: Li, Hang, et al.
Published: (2024)
On the Performance of Linear Adaptive Filters driven by the Ergodic Chaotic Logistic Map
by: Mueller, Andreas
Published: (2025)
by: Mueller, Andreas
Published: (2025)
Data-driven Mori-Zwanzig modeling of Lagrangian particle dynamics in turbulent flows
by: de Wit, Xander, et al.
Published: (2025)
by: de Wit, Xander, et al.
Published: (2025)
Out-of-Domain Generalization in Dynamical Systems Reconstruction
by: Göring, Niclas, et al.
Published: (2024)
by: Göring, Niclas, et al.
Published: (2024)
Physics-Guided Actor-Critic Reinforcement Learning for Swimming in Turbulence
by: Koh, Christopher, et al.
Published: (2024)
by: Koh, Christopher, et al.
Published: (2024)
Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction
by: Hemmer, Christoph Jürgen, et al.
Published: (2024)
by: Hemmer, Christoph Jürgen, et al.
Published: (2024)
Developing cholera outbreak forecasting through qualitative dynamics: Insights into Malawi case study
by: Ghosh, Adrita, et al.
Published: (2025)
by: Ghosh, Adrita, et al.
Published: (2025)
Horizon-Constrained Rashomon Sets for Chaotic Forecasting
by: Kale, Gauri, et al.
Published: (2026)
by: Kale, Gauri, et al.
Published: (2026)
True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics
by: Hemmer, Christoph Jürgen, et al.
Published: (2025)
by: Hemmer, Christoph Jürgen, et al.
Published: (2025)
Similar Items
-
Deficiency of equation-finding approach to data-driven modeling of dynamical systems
by: Zhai, Zheng-Meng, et al.
Published: (2025) -
Invariant Measures in Time-Delay Coordinates for Unique Dynamical System Identification
by: Botvinick-Greenhouse, Jonah, et al.
Published: (2024) -
Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing
by: Norton, Declan A., et al.
Published: (2025) -
Hierarchy of extreme-event predictability in turbulence revealed by machine learning
by: Yang, Yuxuan, et al.
Published: (2026) -
CEBoosting: Online Sparse Identification of Dynamical Systems with Regime Switching by Causation Entropy Boosting
by: Chen, Chuanqi, et al.
Published: (2023)