- Published
- 2022-10-22
- Venue
- Computer Methods in Applied Mechanics and Engineering, vol. 403, pp. 115671
- Cited by
- 736
- Open access
- Yes, bronze
- DOI
- 10.1016/j.cma.2022.115671
Cite this paper
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- APA 7
Wu, C., Zhu, M., Tan, Q., Kartha, Y., & Lu, L. (2022). A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks. Computer Methods in Applied Mechanics and Engineering, 403, 115671. https://doi.org/10.1016/j.cma.2022.115671
- MLA 9
Wu, Chenxi, et al. "A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks." Computer Methods in Applied Mechanics and Engineering, vol. 403, 2022, pp. 115671, https://doi.org/10.1016/j.cma.2022.115671.
- Chicago
Wu, Chenxi, Min Zhu, Qinyang Tan, Yadhu Kartha, and Lu Lu. "A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks." Computer Methods in Applied Mechanics and Engineering 403 (2022): 115671. https://doi.org/10.1016/j.cma.2022.115671.
- GOST
Wu C., Zhu M., Tan Q. [и др.] A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks // Computer Methods in Applied Mechanics and Engineering. — 2022. — Vol. 403. — P. 115671. — URL: https://doi.org/10.1016/j.cma.2022.115671
- BibTeX
@article{wu2022comprehensive, title = {{A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks}}, author = {Chenxi Wu and Min Zhu and Qinyang Tan and Yadhu Kartha and Lu Lu}, journal = {Computer Methods in Applied Mechanics and Engineering}, year = {2022}, volume = {403}, pages = {115671}, doi = {10.1016/j.cma.2022.115671}, url = {https://doi.org/10.1016/j.cma.2022.115671} }- RIS
TY - JOUR AU - Wu, Chenxi AU - Zhu, Min AU - Tan, Qinyang AU - Kartha, Yadhu AU - Lu, Lu TI - A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks JO - Computer Methods in Applied Mechanics and Engineering VL - 403 SP - 115671 PY - 2022 DA - 2022/10/22 DO - 10.1016/j.cma.2022.115671 UR - https://doi.org/10.1016/j.cma.2022.115671 ER -