The Sum-Product Network (SPN) is a new type of machine learning model with fast
exact probabilistic inference over many layers.
Advantages of SPNs:
- Unlike graphical models, SPNs are tractable over high treewidth models
- SPNs are a deep architecture with full probabilistic semantics
- SPNs can incorporate features into an expressive model without requiring approximate inference.
SPNs have achieved impressive results on numerous datasets, including:
- Image completion
- Image classification
- Activity recognition
- Click-through logs
- Nucleic acid sequences
- Collaborative filtering
Also check out awesome-spn, a fantastic curated list of SPN resources, maintained independently from this site.