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Awesome GitHub RepositoriesPartition Function Estimation
Methods for calculating the normalization constant in probabilistic graphical models using sampling techniques.
Distinct from Pseudo-Likelihood Estimation: Candidates cover pseudo-likelihood (avoiding the function) or general MLE, not the estimation of the function itself.
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Awesome Partition Function Estimation GitHub Repositories
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- exacity/deeplearningbook-chinese
exacity/deeplearningbook-chinese
37,285Auf GitHub ansehenThis project is a comprehensive Chinese translation of a technical deep learning textbook, providing an educational resource on the theory and implementation of neural networks. It functions as a collaborative technical translation project designed to make complex academic AI literature accessible to non-English speakers. The project utilizes a community-driven translation model that integrates external suggestions and pull requests to refine linguistic accuracy and reduce bias. It employs standardized terminology mapping to ensure a uniform vocabulary throughout the translated content. To i
Explains the use of importance sampling to calculate model normalization constants.
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