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Alexandre V. Antonov and Vladimir V. Piterbarg develop two strategies for approximating slow-to-calculate features and for conditional anticipated worth calculations: the generalised stochastic sampling (gSS) technique and the useful tensor prepare (fTT) technique, respectively. These are proposed as high-performing options to the generic deep neural networks (DNNs) at the moment routinely really helpful in derivatives pricing and different quantitative finance functions. The
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