Physics-Informed Machine Learning for Optical Fiber Communications: Opportunities and Challenges
Author:
Affiliation:
1. Beijing University of Posts and Telecommunications (BUPT),State Key Laboratory of Information Photonics and Optical Communications,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10209604/10209571/10209949.pdf?arnumber=10209949
Reference25 articles.
1. Physics-Informed Neural Operator for Learning Partial Differential Equations;li;arXiv 2111 03794,2021
2. Learning the solution operator of parametric partial differential equations with physics-informed DeepONets
3. Physics-based deep learning for modeling nonlinear pulse propagation in optical fibers
4. Physics-Based Deep Learning for Fiber-Optic Communication Systems
5. Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
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