Cover Image

Dynamics-Informed Deep Learning for Predicting Extreme Events

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Katsidoniotaki, Eirini, Sapsis, Themistoklis P.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Dynamical Systems Chaotic Dynamics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GEN2: A Generative Prediction-Correction Framework for Long-time Emulations of Spatially-Resolved Climate Extremes
by: Wang, Mengze, et al.
Published: (2025)

Extreme Event Aware ($η$-) Learning
by: Chang, Kai, et al.
Published: (2025)

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)

Active search for Bifurcations
by: Psarellis, Yorgos M., et al.
Published: (2024)

PINN-Obs: Physics-Informed Neural Network-Based Observer for Nonlinear Dynamical Systems
by: Farkane, Ayoub, et al.
Published: (2025)

Backpropagation on Dynamical Networks
by: Tan, Eugene, et al.
Published: (2022)

Machine-Precision Prediction of Low-Dimensional Chaotic Systems
by: Schötz, Christof, et al.
Published: (2025)

Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
by: Brenner, Manuel, et al.
Published: (2022)

CEBoosting: Online Sparse Identification of Dynamical Systems with Regime Switching by Causation Entropy Boosting
by: Chen, Chuanqi, et al.
Published: (2023)

Trans-Bifurcation Prediction of Dynamics in terms of Extreme Learning Machines with Control Inputs
by: Tadokoro, Satoru, 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)

Deep Learning for Prediction and Classifying the Dynamical behaviour of Piecewise Smooth Maps
by: S, Vismaya V, 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)

FEG-Pro: Forecast-Error Growth Profiling for Finite-Horizon Instability Analysis of Nonlinear Time Series
by: Velichko, Andrei, et al.
Published: (2026)

Data-driven forced response analysis with min-max representations of nonlinear restoring forces
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)

Complex fractal trainability boundary can arise from trivial non-convexity
by: Liu, Yizhou
Published: (2024)

Weighted Birkhoff Averages Accelerate Data-Driven Methods
by: Bou-Sakr-El-Tayar, Maria, et al.
Published: (2025)

Predicting Chaotic System Behavior using Machine Learning Techniques
by: Rao, Huaiyuan, et al.
Published: (2024)

Out-of-Domain Generalization in Dynamical Systems Reconstruction
by: Göring, Niclas, et al.
Published: (2024)

Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction
by: Hemmer, Christoph Jürgen, et al.
Published: (2024)

Invariant Measures in Time-Delay Coordinates for Unique Dynamical System Identification
by: Botvinick-Greenhouse, Jonah, et al.
Published: (2024)

Controlling Dynamical Systems into Unseen Target States Using Machine Learning
by: Köglmayr, Daniel, et al.
Published: (2024)

True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics
by: Hemmer, Christoph Jürgen, et al.
Published: (2025)

Extreme Event Precursor Prediction in Turbulent Dynamical Systems via CNN-Augmented Recurrence Analysis
by: Agarwal, Rahul, et al.
Published: (2025)

Physics-Guided Actor-Critic Reinforcement Learning for Swimming in Turbulence
by: Koh, Christopher, et al.
Published: (2024)

Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing
by: Norton, Declan A., et al.
Published: (2025)

Extreme Value Theory with Spectral Techniques: application to a simple attractor
by: Atnip, Jason, et al.
Published: (2020)

Tree-based Learning for High-Fidelity Prediction of Chaos
by: Giammarese, Adam, et al.
Published: (2024)

Network Dynamics-Based Framework for Understanding Deep Neural Networks
by: Lin, Yuchen, et al.
Published: (2025)

Horizon-Constrained Rashomon Sets for Chaotic Forecasting
by: Kale, Gauri, et al.
Published: (2026)

Developing cholera outbreak forecasting through qualitative dynamics: Insights into Malawi case study
by: Ghosh, Adrita, et al.
Published: (2025)

State Estimation Using Sparse DEIM and Recurrent Neural Networks
by: Farazmand, Mohammad
Published: (2024)

Sparse identification of quasipotentials via a combined data-driven method
by: Lin, Bo, et al.
Published: (2024)

Simplicity bias, algorithmic probability, and the random logistic map
by: Hamzi, Boumediene, et al.
Published: (2023)

Stability and Diversity in Collective Adaptation
by: Sato, Yuzuru, et al.
Published: (2004)

A Deep Learning Framework for Identifying Weakly Chaotic, Strongly Chaotic, Resonant and Non-resonant Orbits in the Generalized Kicked Rotator
by: Zu, Jian, et al.
Published: (2025)

Machine Learning for Predicting Chaotic Systems
by: Schötz, Christof, et al.
Published: (2024)

Hierarchy of extreme-event predictability in turbulence revealed by machine learning
by: Yang, Yuxuan, et al.
Published: (2026)

Streams and Graphs of Dynamical Systems
by: De Leo, Roberto, et al.
Published: (2024)