The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Thermodynamics-based Artificial Neural Networks for constitutive modeling
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Raissi, M., Perdikaris, P., & Karniadakis, G. E. (2019) · Journal of Computational Physics · doi:10.1016/j.jcp.2018.10.045 · Cited by 20,384
Approximation by superpositions of a sigmoidal function
Cybenko, G. (1989) · Mathematics of Control, Signals, and Systems · doi:10.1007/bf02551274 · Cited by 13,883
TensorFlow: A system for large-scale machine learning
Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., et al. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.08695 · Cited by 11,822
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2019) · Apollo - University of Cambridge Repository · doi:10.17863/cam.64134 · Cited by 10,460
Automatic Differentiation in Machine Learning: a Survey
Baydin, A. G., Pearlmutter, B. A., Radul, A., & Siskind, J. M. (2015) · Maynooth University ePrints and eTheses Archive (Maynooth University) · Cited by 2,014
SymPy: symbolic computing in Python
Meurer, A., Smith, C. P., Paprocki, M., Čertík, O., Kirpichev, S. B., Rocklin, M., Kumar, A., Ivanov, S., Moore, J. K., Singh, S., et al. (2017) · PeerJ Computer Science · doi:10.7717/peerj-cs.103 · Cited by 1,680
Incorporating Nesterov Momentum into Adam
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Data-driven computational mechanics
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Cited by
A new family of Constitutive Artificial Neural Networks towards automated model discovery
Linka, K., & Kuhl, E. (2023) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/j.cma.2022.115731 · Cited by 281
Metadata
- Authors
- Masi, F., Stefanou, I., Vannucci, P., & Maffi-Berthier, V.
- Venue
- Journal of the Mechanics and Physics of Solids
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 147
- Pages
- 104277
- ISSN
- 0022-5096 (ISSN-L)
- OpenAlex
- W3028072861
- Cited by
- 417
- References
- 36
- FWCI
- 14.36
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Masi, F., Stefanou, I., Vannucci, P., & Maffi-Berthier, V. (2021). Thermodynamics-based Artificial Neural Networks for constitutive modeling. Journal of the Mechanics and Physics of Solids. https://doi.org/10.1016/j.jmps.2020.104277
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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.
