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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorKarssenberg, Derek
dc.contributor.authorFatah, Youssef
dc.date.accessioned2024-08-30T23:02:58Z
dc.date.available2024-08-30T23:02:58Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/47530
dc.description.abstractThis thesis investigates the effectiveness of using ONNX-based machine learning models to simulate cellular automata, specifically focusing on Conway’s Game of Life. The primary goal is to evaluate how well an ONNX-based probabilistic model can replace the traditional deterministic simulation approach used in PCraster, and to assess its ability to represent and predict the behavior of cellular automata.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectA backend for excuting machine learning models stored in the Open Neural Network Exchange format.
dc.titleA backend for excuting machine learning models stored in the Open Neural Network Exchange format.
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsONNX, Software, Machine learning, Cellular automata
dc.subject.courseuuApplied Data Science
dc.thesis.id38104


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