Numerical integration of the Kuramoto Model in Python 3
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Updated
Nov 3, 2017 - Jupyter Notebook
Numerical integration of the Kuramoto Model in Python 3
A python/CUDA pkg which solves numerically the kuramoto model through the Heun's method
The main goal of StDoG is to provide a package which can be used to study dynamical and structural properties (like spectra) on graphs with a large number of vertices.
This repository contains the code for training and visualizing the fully-differentiable Kuramoto model, "KuraNet".
Simple stochastic integrator for the mean field Kuramoto model.
This is a python implementation of Kuramoto model with adaptive rewiring. Adaptive rewiring is meant to simulate the ebb and flow of social interactions.
Simple C++ library for the kuramoto model of syncronization of fireflies.
Kuramoto - Sakaguchi Model Applet
An animation of synchronization of sine functions
Tool to numerically solve and analyse simplicial Kuramoto models.
Matlab code for running the NRPS, RAPS, FEPS and nonlinear Kuramoto models: Models for electric grids that capture the dynamics of synchronous machines and VSMs.
Audio software version of György Ligeti's Poème Symphonique that uses the Kuramoto model and a realtime ML-based sound engine.
I have tried to explain the multi-step-methods of solving ODEs via Adams-Bashforth and Adams-Moulton methods which are explicit and implicit methods respectively. I also have implemented them explicitly to solve for a system of ODEs, I have also done an explicit implementation of fourth order Runge-Kutta method in the process as it is needed.
a handful of custom Max8 abstractions for audio, video and data processing.
A series of simulation codes used to emulate quantum-like networks in the simulation of emergent adaptive behavior, such as network synchronization, and relate the nature of the coupled harmonic oscillators with non-local behavior and chimera states in systems of quantum particles. Coding Used is based on mathematical modelling of transport in q…
[AISTATS 2024] From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach
This is a working repository. Do not expect any clean codes.
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