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Sum-Product Networks A New Deep Architecture Hoifung Poon Dept. Computer Science Eng. University of Washington Seattle WA 98195-2350 hoifung cs. Washington.edu Pedro Domingos pedrod cs. washington.edu Abstract The key limiting factor in graphical model inference and learning is the complexity of the partition function. We thus ask the question what are the most general conditions under which the partition function is tractable The answer leads to a new kind of deep architecture which we call...

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What is sum product networks a?

Sum Product Networks (SPNs) are a type of probabilistic graphical model used for representing and reasoning with probability distributions in a computationally efficient manner.

Who is required to file sum product networks a?

Researchers, data scientists, and anyone working in the field of machine learning or artificial intelligence may use SPNs in their work.

How to fill out sum product networks a?

SPNs are typically constructed using a combination of sum nodes and product nodes, where sum nodes represent additions and product nodes represent multiplications of probability distributions.

What is the purpose of sum product networks a?

The main purpose of SPNs is to efficiently perform probabilistic inference and learn the structure of complex probability distributions.

What information must be reported on sum product networks a?

Information such as the structure of the SPN, the parameters of the probability distributions, and any observed evidence used for inference must be reported.