Qian, Yanxia, Zhang, Yongchao, Huang, Yunqing, and Dong, Suchuan. Physics-informed neural networks for approximating dynamic (hyperbolic) PDEs of second order in time: Error analysis and algorithms. Retrieved from https://par.nsf.gov/biblio/10552406. Journal of Computational Physics 495.C Web. doi:10.1016/j.jcp.2023.112527.

Qian, Yanxia, Zhang, Yongchao, Huang, Yunqing, & Dong, Suchuan. Physics-informed neural networks for approximating dynamic (hyperbolic) PDEs of second order in time: Error analysis and algorithms. Journal of Computational Physics, 495 (C). Retrieved from https://par.nsf.gov/biblio/10552406. https://doi.org/10.1016/j.jcp.2023.112527

Qian, Yanxia, Zhang, Yongchao, Huang, Yunqing, and Dong, Suchuan. "Physics-informed neural networks for approximating dynamic (hyperbolic) PDEs of second order in time: Error analysis and algorithms". Journal of Computational Physics 495 (C). Country unknown/Code not available: Elsevier. https://doi.org/10.1016/j.jcp.2023.112527. https://par.nsf.gov/biblio/10552406.

@article{osti_10552406,
place = {Country unknown/Code not available}, title = {Physics-informed neural networks for approximating dynamic (hyperbolic) PDEs of second order in time: Error analysis and algorithms}, url = {https://par.nsf.gov/biblio/10552406}, DOI = {10.1016/j.jcp.2023.112527}, abstractNote = {}, journal = {Journal of Computational Physics}, volume = {495}, number = {C}, publisher = {Elsevier}, author = {Qian, Yanxia and Zhang, Yongchao and Huang, Yunqing and Dong, Suchuan}, }