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Using Machine Learning to Anticipate Tipping Points and Extrapolate to
  Post-Tipping Dynamics of Non-Stationary Dynamical Systems

Using Machine Learning to Anticipate Tipping Points and Extrapolate to Post-Tipping Dynamics of Non-Stationary Dynamical Systems

Chaos (Chaos), 2022
1 July 2022
Dhruvit Patel
Edward Ott
ArXiv (abs)PDFHTML

Papers citing "Using Machine Learning to Anticipate Tipping Points and Extrapolate to Post-Tipping Dynamics of Non-Stationary Dynamical Systems"

21 / 21 papers shown
Detecting Invariant Manifolds in ReLU-Based RNNs
Detecting Invariant Manifolds in ReLU-Based RNNs
Lukas Eisenmann
Alena Brändle
Zahra Monfared
Daniel Durstewitz
233
2
0
04 Oct 2025
Neural Ordinary Differential Equations for Learning and Extrapolating System Dynamics Across Bifurcations
Neural Ordinary Differential Equations for Learning and Extrapolating System Dynamics Across Bifurcations
Eva van Tegelen
George van Voorn
Ioannis Athanasiadis
Peter van Heijster
225
1
0
25 Jul 2025
Attractor learning for spatiotemporally chaotic dynamical systems using echo state networks with transfer learning
Attractor learning for spatiotemporally chaotic dynamical systems using echo state networks with transfer learning
Mohammad Shah Alam
William Ott
Ilya Timofeyev
184
0
0
30 May 2025
True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics
True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics
Christoph Jürgen Hemmer
Daniel Durstewitz
AI4TSSyDaAI4CE
636
10
0
19 May 2025
Deep Learning for predicting rate-induced tipping
Deep Learning for predicting rate-induced tipping
Yu Huang
S. Bathiany
Peter Ashwin
Niklas Boers
178
28
0
11 Sep 2024
Deep learning for predicting the occurrence of tipping points
Deep learning for predicting the occurrence of tipping points
Chengzuo Zhuge
Jiawei Li
Wei Chen
BDLAI4TS
186
7
0
26 Jul 2024
Out-of-Domain Generalization in Dynamical Systems Reconstruction
Out-of-Domain Generalization in Dynamical Systems Reconstruction
Niclas Alexander Göring
Florian Hess
Manuel Brenner
Zahra Monfared
Daniel Durstewitz
AI4CE
395
29
0
28 Feb 2024
Attractor reconstruction with reservoir computers: The effect of the
  reservoir's conditional Lyapunov exponents on faithful attractor
  reconstruction
Attractor reconstruction with reservoir computers: The effect of the reservoir's conditional Lyapunov exponents on faithful attractor reconstruction
J. D. Hart
287
18
0
30 Dec 2023
Extrapolating tipping points and simulating non-stationary dynamics of
  complex systems using efficient machine learning
Extrapolating tipping points and simulating non-stationary dynamics of complex systems using efficient machine learning
Daniel Köglmayr
Christoph Räth
153
11
0
11 Dec 2023
Tipping Points of Evolving Epidemiological Networks: Machine
  Learning-Assisted, Data-Driven Effective Modeling
Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective ModelingChaos (Chaos), 2023
N. Evangelou
Tianqi Cui
J. M. Bello-Rivas
Alexei Makeev
Ioannis G. Kevrekidis
311
4
0
01 Nov 2023
Bifurcations and loss jumps in RNN training
Bifurcations and loss jumps in RNN trainingNeural Information Processing Systems (NeurIPS), 2023
Lukas Eisenmann
Zahra Monfared
Niclas Alexander Göring
Daniel Durstewitz
467
21
0
26 Oct 2023
Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces
Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces
Miguel Liu-Schiaffini
C. Singer
Nikola B. Kovachki
T. Schneider
Kamyar Azizzadenesheli
Anima Anandkumar
Anima Anandkumar
212
6
0
17 Aug 2023
Detecting disturbances in network-coupled dynamical systems with machine
  learning
Detecting disturbances in network-coupled dynamical systems with machine learningChaos (Chaos), 2023
P. S. Skardal
J. Restrepo
185
4
0
24 Jul 2023
Predicting Ordinary Differential Equations with Transformers
Predicting Ordinary Differential Equations with TransformersInternational Conference on Machine Learning (ICML), 2023
Soren Becker
M. Klein
Alexander Neitz
Giambattista Parascandolo
Niki Kilbertus
306
25
0
24 Jul 2023
Suppressing unknown disturbances to dynamical systems using machine
  learning
Suppressing unknown disturbances to dynamical systems using machine learningCommunications Physics (Commun. Phys.), 2023
J. Restrepo
Clayton P. Byers
P. S. Skardal
345
3
0
19 Jun 2023
Generalized Teacher Forcing for Learning Chaotic Dynamics
Generalized Teacher Forcing for Learning Chaotic DynamicsInternational Conference on Machine Learning (ICML), 2023
Florian Hess
Zahra Monfared
Manuela Brenner
Daniel Durstewitz
AI4CE
411
58
0
07 Jun 2023
Reservoir Computing with Error Correction: Long-term Behaviors of
  Stochastic Dynamical Systems
Reservoir Computing with Error Correction: Long-term Behaviors of Stochastic Dynamical Systems
Cheng Fang
Yubin Lu
Ting Gao
Jinqiao Duan
231
4
0
01 May 2023
Predicting discrete-time bifurcations with deep learning
Predicting discrete-time bifurcations with deep learningNature Communications (Nat. Commun.), 2023
T. Bury
D. Dylewsky
C. Bauch
M. Anand
L. Glass
A. Shrier
G. Bub
201
32
0
16 Mar 2023
Integrating Multimodal Data for Joint Generative Modeling of Complex
  Dynamics
Integrating Multimodal Data for Joint Generative Modeling of Complex DynamicsInternational Conference on Machine Learning (ICML), 2022
Manuela Brenner
Florian Hess
G. Koppe
Daniel Durstewitz
523
17
0
15 Dec 2022
Changes from Classical Statistics to Modern Statistics and Data Science
Changes from Classical Statistics to Modern Statistics and Data Science
Kai Zhang
Shan-Yu Liu
M. Xiong
321
1
0
30 Oct 2022
Catch-22s of reservoir computing
Catch-22s of reservoir computingPhysical Review Research (Phys. Rev. Res.), 2022
Yuanzhao Zhang
Sean P. Cornelius
332
19
0
18 Oct 2022
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