Pages that link to "Item:Q5195186"
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The following pages link to LYAPUNOV EXPONENTS OF THE KURAMOTO–SIVASHINSKY PDE (Q5195186):
Displaying 18 items.
- Analysis of stability, verification and chaos with the Kreiss-Yström equations (Q298406) (← links)
- Error in approximation of Lyapunov exponents on intertial manifolds: the Kuramoto-Sivashinsky equation (Q934161) (← links)
- Lyapunov exponents for the Miles' spherical pendulum equations (Q1808250) (← links)
- Supervised learning from noisy observations: combining machine-learning techniques with data assimilation (Q2077682) (← links)
- Machine learning for prediction with missing dynamics (Q2128320) (← links)
- Lyapunov exponents of the SHE under general initial data (Q2686624) (← links)
- Uncertainty estimates and<i>L</i><sub>2</sub>bounds for the Kuramoto–Sivashinsky equation (Q3412478) (← links)
- Concurrent MultiParameter Learning Demonstrated on the Kuramoto--Sivashinsky Equation (Q5038404) (← links)
- (Q5700927) (← links)
- Order and Disorder in a Cyclically Competitive Ecological Community (Q5887846) (← links)
- Sum of positive Lyapunov exponents for Kuramoto-Sivashinsky equation (Q5945402) (← links)
- Regression-Based Projection for Learning Mori–Zwanzig Operators (Q6084965) (← links)
- Comparison of neural closure models for discretised PDEs (Q6104834) (← links)
- Knowledge-based learning of nonlinear dynamics and chaos (Q6562228) (← links)
- Data-driven reduced-order modeling of spatiotemporal chaos with neural ordinary differential equations (Q6565124) (← links)
- Using machine learning to anticipate tipping points and extrapolate to post-tipping dynamics of non-stationary dynamical systems (Q6572701) (← links)
- Dynamical behaviors and invariant recurrent patterns of Kuramoto-Sivashinsky equation with time-periodic forces (Q6592637) (← links)
- Differentiability in unrolled training of neural physics simulators on transient dynamics (Q6663245) (← links)
