Neural Design Generation
Neural Design Generation is a computational design methodology that leverages neural network architectures to autonomously synthesize artifacts, systems, or forms by learning and generating within high-dimensional design spaces, thereby distinguishing it from rule-based or manual design processes through its reliance on data-driven, learned representations.
16
Publications
522
Citations
57
Authors
27
Institutions
Publications per year
2017–2026
10
Parents
16
Choice Reviews Online · 2016 · 223 citations
Jeffrey Huang, Mikhael Johanes, Frederick Chando Kim et al. · Technology|Architecture + Design · 2021 · 38 citations · Full text
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Cadence Design Systems (United States)
San Jose, United States
1 h-index
3 publications
72 citations
Universitat Politècnica de València
Valencia, Spain
1 h-index
4 publications
100 citations
University of Kent
Canterbury, United Kingdom
1 h-index
1 publications
10 citations
Indian Institute of Technology Kharagpur
Kharagpur, India
1 h-index
1 publications
14 citations

University of North Carolina at Charlotte
Charlotte, United States
1 h-index
3 publications
30 citations

Zhejiang University
Hangzhou, China
1 h-index
2 publications
20 citations

Beijing Normal University
Beijing, China
1 h-index
1 publications
40 citations
National Research Council Canada
Ottawa, Canada
1 h-index
2 publications
28 citations
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TAD · 1 publications · 38 citations
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1 publications · 14 citations
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1 publications · 13 citations
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1 publications · 10 citations
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1 publications · 17 citations
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