Composable inference metaprogramming using subproblems
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
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Inference metaprogramming enables effective probabilistic programming by supporting the decomposition of executions of probabilistic programs into subproblems and the deployment of hybrid probabilistic inference algorithms that apply different base probabilistic inference algorithms to different subproblems. I present the first sound and complete technique for extracting and stitching otherwise entangled subproblems for independent inference. I also prove asymptotic convergence results for hybrid inference algorithms for subproblem inference in probabilistic programs.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 139-142).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.