Evolutionary Neural Design
Evolutionary Neural Design is a computational framework within evolutionary architecture that integrates principles of natural selection and neural network optimization to autonomously generate and refine artificial neural networks through iterative variation, evaluation, and selection processes.
52
Publications
3.5K
Citations
157
Authors
75
Institutions
Publications per year
2017–2026
15
Parents
52
Designing neural networks through neuroevolution
Kenneth O. Stanley, Jeff Clune, Joel Lehman et al. · Nature Machine Intelligence · 2018 · 689 citations
Autonomous deep learning: A genetic DCNN designer for image classification
Benteng Ma, Xiang Li, Yong Xia et al. · Neurocomputing · 2019 · 115 citations
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Razi University
Kermanshah, Iran
3 h-index
11 publications
743 citations

Sichuan University
Chengdu, China
2 h-index
6 publications
255 citations

Universidad Carlos III de Madrid
Madrid, Spain
2 h-index
6 publications
231 citations
Chengdu University
Chengdu, China
2 h-index
6 publications
255 citations
University of Guilan
Rasht, Iran
2 h-index
5 publications
404 citations

Oklahoma State University
Stillwater, United States
2 h-index
2 publications
85 citations
University of Guelph
Guelph, Canada
2 h-index
3 publications
133 citations

Victoria University of Wellington
Wellington, New Zealand
1 h-index
2 publications
54 citations
1–8 of 75
Repository · 2 publications · 28 citations
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2 publications · 42 citations
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2 publications · 118 citations
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2 publications · 85 citations
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2 publications · 55 citations
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