Towards formal verification of Bayesian inference in probabilistic programming via guaranteed bounds
<p>Probabilistic models are an indispensable tool in many scientific fields, from the social and medical sciences to physics and machine learning. In probabilistic programming, such models are specified as computer programs: a flexible yet precise representation that allows for automated analy...
Main Author: | Zaiser, F |
---|---|
Other Authors: | Murawski, A |
Format: | Thesis |
Language: | English |
Published: |
2024
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Subjects: |
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