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Model dynamic networks with metadata using dynamic SBMs, with parameters inferred through belief propagation

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DSBMM-BP

Model dynamic networks with metadata using dynamic SBMs, with parameters inferred through belief propagation.

Implemented purely in Python, with relatively high performance and parallelisation through use of Numba. PyPI package to follow shortly!

Roadmap:

  • [DONE] Simulation module
  • [DONE] Base model class module
  • [Consider later] Data loader module
  • [DONE] Application module
  • [DONE] Processor module
  • [In progress] Subsequent model class modules
  • [In progress] Tests

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Model dynamic networks with metadata using dynamic SBMs, with parameters inferred through belief propagation

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