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Deriving conditional and marginal distributions using conjugacy relationshipscan be time consuming and error prone. In this paper, we propose a strategy forautomating such derivations. Unlike previous systems which focus onrelationships between pairs of random variables, our system (which we callAutoconj) operates directly on Python functions that compute log-jointdistribution functions. Autoconj provides support for conjugacy-exploitingalgorithms in any Python embedded PPL. This paves the way for acceleratingdevelopment of novel inference algorithms and structure-exploiting modelingstrategies.

Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language