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Jae-eun Park

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Machine learning based co-creative design framework

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Jan 23, 2020
Brian Quanz, Wei Sun, Ajay Deshpande, Dhruv Shah, Jae-eun Park

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We propose a flexible, co-creative framework bringing together multiple machine learning techniques to assist human users to efficiently produce effective creative designs. We demonstrate its potential with a perfume bottle design case study, including human evaluation and quantitative and qualitative analyses.

* Thirty-third Conference on Neural Information Processing Systems (NeurIPS) 2019 Workshop on Machine Learning for Creativity and Design, December 14th, 2019, Vancouver, Canada (https://neurips2019creativity.github.io/) 
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