The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
hp-VPINNs: Variational physics-informed neural networks with domain decomposition
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Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946
Raissi, M., Perdikaris, P., & Karniadakis, G. E. (2019) · Journal of Computational Physics · doi:10.1016/j.jcp.2018.10.045 · Cited by 20,384
Self-citationDaubechies, I. (1992) · doi:10.1137/1.9781611970104 · Cited by 15,979
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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
An Introduction To Compressive Sampling
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DeepXDE: A Deep Learning Library for Solving Differential Equations
Lu, L., Meng, X., Mao, Z., & Karniadakis, G. E. (2021) · SIAM Review · doi:10.1137/19m1274067 · Cited by 2,512
Self-citationDGM: A deep learning algorithm for solving partial differential equations
Sirignano, J., & Spiliopoulos, K. (2018) · Journal of Computational Physics · doi:10.1016/j.jcp.2018.08.029 · Cited by 2,208
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Cited by
Physics-informed machine learning
Karniadakis, G. E., Kevrekidis, I. G., Lu, L., Perdikaris, P., Wang, S., & Yang, L. (2021) · Nature Reviews Physics · doi:10.1038/s42254-021-00314-5 · Cited by 8,718
Self-citationPhysics-informed neural networks (PINNs) for fluid mechanics: a review
Cai, S., Mao, Z., Wang, Z., Yin, M., & Karniadakis, G. E. (2021) · Acta Mechanica Sinica · doi:10.1007/s10409-021-01148-1 · Cited by 2,084
Self-citationPhysics-Informed Neural Networks for Heat Transfer Problems
Cai, S., Wang, Z., Wang, S., Perdikaris, P., & Karniadakis, G. E. (2021) · Journal of Heat Transfer · doi:10.1115/1.4050542 · Cited by 1,312
Self-citationGao, H., Sun, L., & Wang, J.-X. (2021) · Journal of Computational Physics · doi:10.1016/j.jcp.2020.110079 · Cited by 621
Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons
Psaros, A. F., Meng, X., Zou, Z., Guo, L., & Karniadakis, G. E. (2023) · Journal of Computational Physics · doi:10.1016/j.jcp.2022.111902 · Cited by 455
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Metadata
- Authors
- Kharazmi, E., Zhang, Z., & Karniadakis, G. E. M.
- Venue
- Computer Methods in Applied Mechanics and Engineering
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 374
- Pages
- 113547
- ISSN
- 0045-7825 (ISSN-L)
- OpenAlex
- W3011806874
- Cited by
- 818
- References
- 49
- FWCI
- 24.71
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Kharazmi, E., Zhang, Z., & Karniadakis, G. E. M. (2021). hp-VPINNs: Variational physics-informed neural networks with domain decomposition. Computer Methods in Applied Mechanics and Engineering. https://doi.org/10.1016/j.cma.2020.113547
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