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Differential machine learning combines automatic adjoint differentiation (AAD) with modern machine learning (ML) in the context of risk management of financial Derivatives.
A nonparametric approach to pricing and hedging derivative securities via learning networks
J. M. Hutchinson, A. W. Lo, and T. Poggio · 1994
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Valuation of the early-exercise price for options using simulations and nonparametric regression
J. F. Carriere · 1996
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The market model of interest rate dynamics
A. Brace, D. Gatarek, and M. Musiela · 1997
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Valuing american options by simulation: A simple least-square approach
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Pricing american options: A duality approach
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Smoking adjoints: Fast evaluation of greeks in monte carlo calculations
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The quadratic rough heston model and the joint s&p 500/vix smile calibration problem
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Q. Chan-Wai-Nam, J. Mikael, and X. Warin · 2018
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Aad and backpropagation in machine learning and finance, explained in 15min
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