Funder
Swiss National Foundation
FARE
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,General Engineering,Theoretical Computer Science,Software,Applied Mathematics,Computational Mathematics,Numerical Analysis
Reference52 articles.
1. Han, J., Jentzen, A., E, W.: Solving high-dimensional partial differential equations using deep learning. Proc. Natl. Acad. Sci. 115(34), 8505–8510 (2018)
2. E, W., Han, J., Jentzen, A.: Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations. Commun. Math. Stat. 5(4):349–380 (2017). https://doi.org/10.1007/s40304-017-0117-6
3. Bellman, R.: English Dynamic Programming, vol. XXV. Princeton University Press, Princeton, NJ (1957)
4. Beck, C., Becker, S., Cheridito, P., Jentzen, A., Neufeld, A.: Deep splitting method for parabolic PDEs. arXiv:1907.03452 (2019)
5. Chan-Wai-Nam, Q., Mikael, J., Warin, X.: Machine learning for semi linear PDEs. J. Sci. Comput. 79(3), 1667–1712 (2019). https://doi.org/10.1007/s10915-019-00908-3
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献