1. On learning the derivatives of an unknown mapping with multilayer feedforward networks
2. Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
3. Deeponet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators[J];lu;arXiv preprint arXiv 1910 03759,2019
4. Physics-Informed Neural Operator for Fast and Scalable Optical Fiber Channel Modelling in Multi-Span Transmission;song;2022 European Conference on Optical Communications (ECOC),2022
5. Fourier Neural Operator Based Fibre Channel Modelling for Optical Transmission[C];qiu;European Conference and Exhibition on Optical Communication,2022