Sum Product Flow: An Easy and Extensible Library for Sum-Product Networks
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Updated
Sep 22, 2024 - Python
Sum Product Flow: An Easy and Extensible Library for Sum-Product Networks
GraphSPNs: Sum-Product Networks Benefit From Canonical Orderings
Probabilistic programming system for fast and exact symbolic inference
An implementation of EinsumNetworks in PyTorch.
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs
Probabilistic Circuits in Julia
🔆 A Python implementation of a sum-product network with gaussian processes leafs model (SPNGP, arXiv:1809.04400) 📃
A Python Library for Deep Probabilistic Modeling
Sum-product networks in Julia.
Implementation of DeepDB: Learn from Data, not from Queries!
Survey and presentation about Sum-Product Networks (SPNs)
Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)
PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
The first Scala-based library for Sum-Product Networks
Personal fork of the official EinsumNetworks implementation with a few enhancements.
A structured list of resources about Sum-Product Networks (SPNs)
Tractable Machine Learning in Cosmological Structure Formation.
Sum-Product Networks (SPNs) for Robust Automatic Speaker Identification.
Barebone slides introducing sum-product networks.
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