https://github.com/pavanchaggar/graphodebenchmark
https://github.com/pavanchaggar/graphodebenchmark
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/pavanchaggar/graphodebenchmark
- Owner: PavanChaggar
- Created: 2021-06-21T12:03:22.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2021-10-15T13:45:12.000Z (over 3 years ago)
- Last Synced: 2025-01-18T04:06:39.826Z (5 months ago)
- Language: Python
- Size: 85.1 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
This repo contains code to benchmark the inference of ODE models on graphs usingjulia and python. For inference in julia, [Turing](https://github.com/TuringLang/Turing.jl) will be used; for python, [numpyro](https://github.com/pyro-ppl/numpyro) will be used.
The system used will be:
where $\mathbf{L}$ is the graph Laplacian given by:
where $\mathbf{D}$ and $\mathbf{A}$ are the degree and adjacency matrices, respectively.
The model is version of the Fisher-Kolmogorov–Petrovsky–Piskunov equation defined on a discete domain, namely a graph. In this case, we will use a Erdos-Renyi random graph of varying size and connection probability.