Integral Transforms in a Physics-Informed (Quantum) Neural Network setting: Applications & Use-Cases. (arXiv:2206.14184v1 [quant-ph])

In many computational problems in engineering and science, function or model
differentiation is essential, but also integration is needed. An important
class of computational problems include so-called integro-differential
equations which include both integrals and derivatives of a function. In
another example, stochastic differential equations can be written in terms of a
partial differential equation of a probability density function of the
stochastic variable. To learn characteristics of the stochastic variable based
on the density function, specific integral transforms, namely moments, …

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