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Parabolic partial differential equations (PDEs) are widely used in the mathematical modeling of natural phenomena and man made complex systems.
Branching diffusion processes
Skorokhod, A. V · 1964
Earlier work this paper cites.
On the branching process for brownian particles with an absorbing boundary
Watanabe, S · 1965
Earlier work this paper cites.
Dynamic programming
Bellman, R · 1966
Earlier work this paper cites.
The pricing of options and corporate liabilities
Black, F., and Scholes, M · 1973
Earlier work this paper cites.
Theory of rational option pricing
Merton, R. C · 1973
Earlier work this paper cites.
Application of brownian motion to the equation of kolmogorov-petrovskii-piskunov
McKean, H. P · 1975
Earlier work this paper cites.
Galerkin finite element methods for parabolic problems
Thomée, V · 1984
Earlier work this paper cites.
Adapted solution of a backward stochastic differential equation
Pardoux, E., and Peng, S · 1990
Earlier work this paper cites.
Backward stochastic differential equations and quasilinear parabolic partial differential equations
Pardoux, E., and Peng, S · 1992
Earlier work this paper cites.
Solving forward-backward stochastic differential equations explicitly—a four step scheme
Ma, J., Protter, P., and Yong, J. M · 1994
Earlier work this paper cites.
Numerical integration of stochastic differential equations
Milstein, G. N · 1994
Earlier work this paper cites.
Numerical methods for forward-backward stochastic differential equations
Douglas, Jr., J., Ma, J., and Protter, P · 1996
Earlier work this paper cites.
Recursive valuation of defaultable securities and the timing of resolution of uncertainty
Duffie, D., Schroder, M., Skiadas, C., et al · 1996
Earlier work this paper cites.
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Ma, J., and Yong, J · 1999
Earlier work this paper cites.
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Pardoux, E., and Tang, S · 1999
Earlier work this paper cites.
Difference equations and inequalities: theory, methods, and applications
Agarwal, R. P · 2000
Earlier work this paper cites.
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Ma, J., Protter, P., San Martín, J., and Torres, S · 2002
Earlier work this paper cites.
A quantization algorithm for solving multidimensional discrete-time optimal stopping problems
Bally, V., Pages, G., et al · 2003
Earlier work this paper cites.
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Bouchard, B., and Touzi, N · 2004
Earlier work this paper cites.
Numerical solution of parabolic equations in high dimensions
Von Petersdorff, T., and Schwab, C · 2004
Earlier work this paper cites.
A numerical scheme for BSDEs
Zhang, J · 2004
Earlier work this paper cites.
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Gobet, E., Lemor, J.-P., Warin, X., et al · 2005
Earlier work this paper cites.
A forward-backward stochastic algorithm for quasi-linear PDEs
Delarue, F., and Menozzi, S · 2006
Earlier work this paper cites.
Rate of convergence of an empirical regression method for solving generalized backward stochastic differential equations
Lemor, J.-P., Gobet, E., Warin, X., et al · 2006
Earlier work this paper cites.
Numerical algorithms for forward-backward stochastic differential equations
Milstein, G. N., and Tretyakov, M. V · 2006
Earlier work this paper cites.
A forward scheme for backward sdes
Bender, C., and Denk, R · 2007
Earlier work this paper cites.
Second-order backward stochastic differential equations and fully nonlinear parabolic pdes
Cheridito, P., Soner, H. M., Touzi, N., and Victoir, N · 2007
Earlier work this paper cites.
Discretization of forward-backward stochastic differential equations and related quasi-linear parabolic equations
Milstein, G. N., and Tretyakov, M. V · 2007
Earlier work this paper cites.
A concise course on stochastic partial differential equations
Prévôt, C., and Röckner, M · 2007
Earlier work this paper cites.
Numerical simulation of bsdes using empirical regression methods: theory and practice
Gobet, E., and Lemor, J.-P · 2008
Earlier work this paper cites.
Tractability of Multivariate Problems: Standard information for functionals
Novak, E., and Woźniakowski, H · 2008
Earlier work this paper cites.
Discrete-time approximation of bsdes and probabilistic schemes for fully nonlinear pdes
Bouchard, B., Elie, R., and Touzi, N · 2009
Earlier work this paper cites.
Discrete-time approximation of BSDEs and probabilistic schemes for fully nonlinear PDEs
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Earlier work this paper cites.
Numerical solution of helmholtz equation by the modified hopfield finite difference techniques
Dehghan, M., Nourian, M., and Menhaj, M. B · 2009
Earlier work this paper cites.
Probabilistic methods for semilinear partial differential equations. Applications to finance
Crisan, D., and Manolarakis, K · 2010
Earlier work this paper cites.
On the Monte Carlo simulation of BSDEs: an improvement on the Malliavin weights
Crisan, D., Manolarakis, K., and Touzi, N · 2010
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Da Prato, G., Jentzen, A., and Röckner, M · 2010
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Solving BSDE with adaptive control variate
Gobet, E., and Labart, C · 2010
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Monte Carlo solution of Cauchy problem for a nonlinear parabolic equation
Rasulov, A., Raimova, G., and Mascagni, M · 2010
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Burgard, C., and Kjaer, M · 2011
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Cox, S., Hutzenthaler, M., Jentzen, A., van Neerven, J., and Welti, T · 2016
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Multilevel picard iterations for solving smooth semilinear parabolic heat equations
E, W., Hutzenthaler, M., Jentzen, A., and Kruse, T · 2016
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Simulation of BSDEs with jumps by Wiener chaos expansion
Geiss, C., and Labart, C · 2016
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Stratified regression monte-carlo scheme for semilinear pdes and bsdes with large scale parallelization on gpus
Gobet, E., López-Salas, J. G., Turkedjiev, P., and Vázquez, C · 2016
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Counterparty risk valuation: A marked branching diffusion approach
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Brownian motion and stochastic calculus
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A dual method for backward stochastic differential equations with application to risk valuation
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Becker, S., Cheridito, P., and Jentzen, A · 2018
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A unified deep artificial neural network approach to partial differential equations in complex geometries
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Chan-Wai-Nam, Q., Mikael, J., and Warin, X · 2018
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He, J., Li, L., Xu, J., and Zheng, C · 2018
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A deep neural network surrogate for high-dimensional random partial differential equations
Nabian, M. A., and Meidani, H · 2018
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Raissi, M · 2018
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Dgm: A deep learning algorithm for solving partial differential equations
Sirignano, J., and Spiliopoulos, K · 2018
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Monte carlo for high-dimensional degenerated semi linear and full non linear pdes
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Nesting monte carlo for high-dimensional non-linear pdes
Warin, X · 2018
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