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Deep learning delay coordinate dynamics for chaotic attractors from
  partial observable data

Deep learning delay coordinate dynamics for chaotic attractors from partial observable data

20 November 2022
Charles D. Young
M. Graham
ArXiv (abs)PDFHTML

Papers citing "Deep learning delay coordinate dynamics for chaotic attractors from partial observable data"

5 / 5 papers shown
Title
Invariant Measures for Data-Driven Dynamical System Identification: Analysis and Application
Jonah Botvinick-Greenhouse
94
0
0
31 Jan 2025
On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions
On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions
Jake Buzhardt
C. Ricardo Constante-Amores
Michael D. Graham
171
2
0
20 Nov 2024
Measure-Theoretic Time-Delay Embedding
Measure-Theoretic Time-Delay Embedding
Jonah Botvinick-Greenhouse
Maria Oprea
R. Maulik
Yunan Yang
73
2
0
13 Sep 2024
Forecasting the Forced van der Pol Equation with Frequent Phase Shifts
  Using Reservoir Computing
Forecasting the Forced van der Pol Equation with Frequent Phase Shifts Using Reservoir Computing
Sho Kuno
Hiroshi Kori
55
0
0
23 Apr 2024
Dynamics of a data-driven low-dimensional model of turbulent minimal
  Couette flow
Dynamics of a data-driven low-dimensional model of turbulent minimal Couette flow
Alec J. Linot
M. Graham
AI4CE
55
22
0
11 Jan 2023
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