(Reproduction)Sum-product network implementation and its application to image completion.
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Updated
May 30, 2019 - C++
(Reproduction)Sum-product network implementation and its application to image completion.
Survey and presentation about Sum-Product Networks (SPNs)
Tractable Machine Learning in Cosmological Structure Formation.
Simple implementation (in Go) of algorithm to convert SPNs into BNs with ADDs.
replication of this paper: https://www.nrl.navy.mil/itd/aic/content/evaluation-sum-product-networks-image-classification-tasks
The first Scala-based library for Sum-Product Networks
Optimisation of Overparametrized Sum-Product Networks
GoDrive is an application of autonomous driving through image classification using sum-product networks.
Personal fork of the official EinsumNetworks implementation with a few enhancements.
Barebone slides introducing sum-product networks.
Safe Semi-Supervised Learning of Sum-Product Networks
DeepNotebooks is an automated statistical analysis tool build on top of SPNs. They are currently being developed by Claas Völcker at the ML group at TU Darmstadt.
Code and supplemental material for "Sum-Product Autoencoding: Encoding and Decoding Representations using Sum-Product Networks"
Probabilistic Circuits in Julia
Sum-Product Networks (SPNs) for Robust Automatic Speaker Identification.
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
An implementation of EinsumNetworks in PyTorch.
🔆 A Python implementation of a sum-product network with gaussian processes leafs model (SPNGP, arXiv:1809.04400) 📃
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