Topic: kuramoto-sivashinsky Goto Github
Some thing interesting about kuramoto-sivashinsky
Some thing interesting about kuramoto-sivashinsky
kuramoto-sivashinsky,A Python package to simulate and measure chaotic dynamical systems.
User: duncdennis
Home Page: https://duncdennis.github.io/lorenzpy/
kuramoto-sivashinsky,Code for the Modeling From Measurements report
User: f-rosato
kuramoto-sivashinsky,pseudospectral (fourier) solutions of a few 1-dimensional PDEs
User: markmbaum
kuramoto-sivashinsky,An AOT-based algorithm to estimate multiple unknown parameters in the Kuramoto-Saviashinski equation. Source code for the paper "Concurrent Multiparameter Learning Demonstrated on the Kuramoto-Sivashinsky Equation" by Pachev, Whitehead, and McQuarrie.
Organization: parametric-data-assimilation
Home Page: https://epubs.siam.org/doi/abs/10.1137/21M1426109
kuramoto-sivashinsky,Framework to learn effective dynamics and couple a macro scale simulator with a fast neural network latent propagator.
User: pvlachas
Home Page: https://github.com/cselab/LED
kuramoto-sivashinsky,RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.
User: pvlachas
Home Page: https://www.cse-lab.ethz.ch
kuramoto-sivashinsky,Numerical Evidence for Sample Efficiency of Model-Based over Model-Free Reinforcement Learning Control of Partial Differential Equations [ECC'24]
User: stwerner97
kuramoto-sivashinsky,Runge-Kutta adaptive-step solvers for nonlinear PDEs. Solvers include both exponential time differencing and integrating factor methods.
User: whalenpt
kuramoto-sivashinsky,Spectral Integration and Differentiation Algorithms. Includes FFTs, Chebyshev Transforms, and Hankel transforms. Exponential time differencing and integrating factor Runge-Kutta methods.
User: whalenpt
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