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Deep backward stochastic differential equation method is a numerical method that truc deep learning with Backward stochastic differential equation (BSDE). This method is particularly useful expérience solving high-dimensional problems in financial mathematics. By leveraging the powerful function approximation capabilities of deep neural networks, deep BSDE addresses the computational conflit faced by traditional numerical methods in high-dimensional settings.
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