In the frame of the course Graphical Models discrete inference and learning, we implemented Loopy Belief Propagation (LBP) and Supervised Belief Propagation (SBP) from the paper "Supervised Belief Propagation: Scalable Supervised Inference on Attributed Networks" https://ieeexplore.ieee.org/abstract/document/8215532 on the MoovieLens dataset mentioned in the report.
- Graphical models implementation can be found in the file graph_models.py
- LBP and SBP implementations can be found in belief_propagation.py
- main.ipynb is a notebook allowing to run the implemented methods. More experiments can be added from the methods in belief_propagation.py