How Analysis Can Teach Us the Optimal Way to Design Neural Operators
How Analysis Can Teach Us the Optimal Way to Design Neural Operators
This paper presents a mathematics-informed approach to neural operator design, building upon the theoretical framework established in our prior work. By integrating rigorous mathematical analysis with practical design strategies, we aim to enhance the stability, convergence, generalization, and computational efficiency of neural operators. We revisit key theoretical insights, including stability …