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Deep Learning and Elicitability for McKean-Vlasov FBSDEs With Common Noise
We present a novel numerical method for solving McKean-Vlasov forward-backward stochastic differential equations (MV--FBSDEs) with common noise, combining Picard iterations, elicitability and deep learning. The key innovation involves elicitability to derive a path-wise loss function, enabling effic
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