most citedStochastic loss reserving with mixture density neural networks

14 citations · 14 across the 1 of their papers we have counts for

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stat.ME2021★ 14 cited

Stochastic loss reserving with mixture density neural networks

Muhammed Taher Al-Mudafer, Benjamin Avanzi, Greg Taylor +1

Neural networks offer a versatile, flexible and accurate approach to loss reserving. However, such applications have focused primarily on the (important) problem of fitting accurat…