a python framework to build, learn and reason about probabilistic circuits and tensor networks
A Python Library for Deep Probabilistic Modeling
How to Turn Your Knowledge Graph Embeddings into Generative Models
Squared Non-monotonic Probabilistic Circuits
PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
GraphSPNs: Sum-Product Networks Benefit From Canonical Orderings
Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs
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