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Automatic Code Generation for Statistical Models with Augmentation and Collapsing

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thesis
posted on 19.01.2021, 04:37 by SACHITH HASARANGA SENEVIRATNE
This thesis presents a system for automatically generating code for a set of Bayesian statistical models. The overall contributions include a system for performing pattern matching and symbolic computations, a schema system of efficiently managing statistical operations in a reusable manner. Additionally, the overall system for generating efficient code is also presented, alongside the general architecture that enables this process.

History

Campus location

Australia

Principal supervisor

Wray Buntine

Additional supervisor 1

Lan Du

Year of Award

2021

Department, School or Centre

Clayton School of IT

Course

Doctor of Philosophy

Degree Type

DOCTORATE