The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
De novo composite design based on machine learning algorithm
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Data Mining: Practical Machine Learning Tools and Techniques
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TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., et al. (2016) · arXiv · doi:10.48550/arxiv.1603.04467 · Cited by 9,408
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Selection of relevant features and examples in machine learning
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Fiber-reinforced composites : materials, manufacturing, and design
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Magnetic Soft Materials and Robots
Kim, Y., & Zhao, X. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00481 · Cited by 873
Diez-Olivan, A., Del Ser, J., Galar, D., & Sierra, B. (2019) · Information Fusion · doi:10.1016/j.inffus.2018.10.005 · Cited by 633
Gu, G. X., Chen, C.-T., Richmond, D. J., & Buehler, M. J. (2018) · Materials Horizons · doi:10.1039/c8mh00653a · Cited by 556
Self-citationBeautiful and Functional: A Review of Biomimetic Design in Additive Manufacturing
du Plessis, A., Broeckhoven, C., Yadroitsava, I., Yadroitsev, I., Hands, C. H., Kunju, R., & Bhate, D. (2019) · Additive Manufacturing · doi:10.1016/j.addma.2019.03.033 · Cited by 448
Deep learning model to predict complex stress and strain fields in hierarchical composites
Yang, Z., Yu, C.-H., & Buehler, M. J. (2021) · Science Advances · doi:10.1126/sciadv.abd7416 · Cited by 389
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Metadata
- Authors
- Gu, G. X., Chen, C.-T., & Buehler, M. J.
- Venue
- Extreme Mechanics Letters
- Publisher
- Elsevier BV
- Published
- 2018-01
- Volume
- 18
- Pages
- 19-28
- ISSN
- 2352-4316 (ISSN-L)
- OpenAlex
- W2766966300
- Cited by
- 470
- References
- 36
- FWCI
- 10.84
- Type
- journal article
- Language
- en
- Open access
- bronze
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- The paper
- Gu, G. X., Chen, C.-T., & Buehler, M. J. (2018). De novo composite design based on machine learning algorithm. Extreme Mechanics Letters. https://doi.org/10.1016/j.eml.2017.10.001
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
