/dd_networkgen

Primary LanguageJupyter NotebookGNU General Public License v2.0GPL-2.0

Data-driven FEP Network Generation

Dev environment for creation of a workflow that uses ML models to predict SEM on fully-connected FEP networks, then uses DiffNet to create a statistically optimal set of edges to simulate. Currently builds on DiffNet 63da350.

Authors:

  • J. Scheen
  • J. Michel