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We propose an algorithm which predicts each subsequent time step relative tothe previous timestep of intractable short rate model (when adjusted for driftand overall distribution of previous percentile result) and show that themethod achieves superior outcomes to the unbiased estimate both on the traineddataset and different validation data.

Approximating intractable short ratemodel distribution with neural network