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Found 3 papers, 1 papers with code
Soft Learning Probabilistic Circuits
This paper focuses on the main algorithm for training PCs, LearnSPN, a gold standard due to its efficiency, performance, and ease of use, in particular for tabular data.
Probabilistic Circuits with Constraints via Convex Optimization
This work addresses integrating probabilistic propositional logic constraints into the distribution encoded by a probabilistic circuit (PC).
Toward Robust Uncertainty Estimation with Random Activation Functions
Deep neural networks are in the limelight of machine learning with their excellent performance in many data-driven applications.
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