Design Representation Learning
Design Representation Learning is a computational framework in Evolutionary Product Design that systematically acquires and encodes latent design knowledge from product data through algorithmic models, distinguishing itself by enabling automated, data-driven generalization of design principles for generative innovation.
154
Publications
6.8K
Citations
430
Authors
173
Institutions
Publications per year
2017–2026
99
Parents
154
1–5 of 154
430
5
h-index
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1–5 of 430
173
Carnegie Mellon University
Pittsburgh, United States
10 h-index
22 publications
680 citations
Massachusetts Institute of Technology
Cambridge, United States
10 h-index
20 publications
2.2K citations

Pennsylvania State University
State College, United States
6 h-index
12 publications
391 citations

Zhejiang University
Hangzhou, China
5 h-index
11 publications
453 citations
Northwestern University
Evanston, United States
4 h-index
11 publications
829 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
9 publications
257 citations
University of Michigan
Ann Arbor, United States
4 h-index
18 publications
792 citations
Honda (Germany)
Frankfurt am Main, Germany
4 h-index
12 publications
300 citations
1–8 of 173
13 publications · 613 citations
13
h-index
7 publications · 211 citations
7
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CACAIE · 4 publications · 290 citations
4
h-index
4 publications · 174 citations
4
h-index
IJAC · 3 publications · 135 citations
3
h-index
1–5