https://github.com/pavanchaggar/networkinference
Implementing network models, comparing with data and performing Bayesian Inference
https://github.com/pavanchaggar/networkinference
Last synced: 3 months ago
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Implementing network models, comparing with data and performing Bayesian Inference
- Host: GitHub
- URL: https://github.com/pavanchaggar/networkinference
- Owner: PavanChaggar
- Created: 2020-08-21T11:03:54.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2021-03-17T09:47:33.000Z (about 4 years ago)
- Last Synced: 2025-01-18T04:06:35.910Z (5 months ago)
- Language: Jupyter Notebook
- Size: 73.3 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 3
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Metadata Files:
- Readme: README.md
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README
# Network Inference
This repository houses progress toward creating a flexible inference framework for network brain modelling of protein propagation.
The current goals are to implement:
- [x] Simulations of protein propagation on brain networks using network diffusion models and Fisher-Kolmogorov–Petrovsky–Piskunov (FKPP) models.
- [ ] Perform inference using sampling methods such as Markov chain Monte Carlo (MCMC), variational inference and simulation based inference.
- [ ] Compare the efficacy and efficiency of these algorithms with variably sized free parameter sets and network sizes.
Work in progress documentation can be found [here](https://pavanchaggar.github.io/NetworkInference/intro.html).