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Integral Transforms in a Physics-Informed (Quantum) Neural Network setting: Applications & Use-Cases. (arXiv:2206.14184v1 [quant-ph])
stat.ML updates on arXiv.org arxiv.org
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, …
applications arxiv cases network neural network physics quantum