Data-Driven Bicycle Design using Performance-Aware Deep Generative Models
This treatise explores the application of Deep Generative Machine Learning Models to bicycle design and optimization. Deep Generative Models have been growing in popularity across the design community thanks to their ability to learn and mimic complex data distributions. This work addresses several...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/144624 |