A samplewise backpropagation method for neural networks driven by fractional Brownian motion
A fractional stochastic neural network with residual dynamics driven by fractional Brownian motion is developed by introducing a discrete stochastic maximum principle and constructing the corresponding adjoint recursion.
Yuecai Han, Jianming Xu
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