Author:
Naito Riu,Yamada Toshihiro
Funder
Japan Science and Technology Agency
Publisher
Springer Science and Business Media LLC
Reference54 articles.
1. Arora, R., Basu, A., Mianjy, P., & Mukherjee, A. (2018). Understanding deep neural networks with rectified linear units. Vancouver.
2. Beck, C., Becker, S., Cheridito, P., Jentzen, A., & Neufeld, A. (2021). Deep splitting method for parabolic PDEs. SIAM Journal on Scientific Computing, 43(5), 3135–3154.
3. Berner, J., Grohs, P., & Jentzen, A. (2020). Analysis of the generalization error: Empirical risk minimization over deep artificial neural networks overcomes the curse of dimensionality in the numerical approximation of Black–Scholes partial differential equations. SIAM Journal on Mathematics of Data Science, 2(3), 631–657.
4. Bouchard, B., Tan, X., Warin, X., & Zou, Y. (2017). Numerical approximation of BSDEs using local polynomial drivers and branching processes. Monte Carlo Methods and Applications, 23(4), 241–263.
5. Calin, O. (2020). Deep Learning Architectures. Springer.
Cited by
1 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
1. Deep Learning-Based Expansion Around Elliptic Diffusions;2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE);2023-12-04