The following pages link to (Q4029028):
Displaying 50 items.
- An SGBM-XVA demonstrator: a scalable Python tool for pricing XVA (Q1980957) (← links)
- BSDE with rcll reflecting barrier driven by a Lévy process (Q1986117) (← links)
- Martingale driven BSDEs, PDEs and other related deterministic problems (Q1994914) (← links)
- Strong-viscosity solutions: classical and path-dependent PDEs (Q2002602) (← links)
- Numerical methods for a class of nonlocal diffusion problems with the use of backward SDEs (Q2007289) (← links)
- Mean-field anticipated BSDEs driven by fractional Brownian motion and related stochastic control problem (Q2009377) (← links)
- Interior gradient and Hessian estimates for the Dirichlet problem of semi-linear degenerate elliptic systems: a probabilistic approach (Q2010418) (← links)
- Stochastic optimization theory of backward stochastic differential equations driven by G-Brownian motion (Q2015746) (← links)
- A Bismut-Elworthy formula for quadratic BSDEs (Q2018566) (← links)
- Anticipated backward stochastic differential equations driven by the Teugels martingales (Q2019174) (← links)
- Singular limit of BSDEs and optimal control of two scale stochastic systems in infinite dimensional spaces (Q2020319) (← links)
- Infinite horizon forward-backward doubly stochastic differential equations and related SPDEs (Q2025173) (← links)
- The link between stochastic differential equations with non-Markovian coefficients and backward stochastic partial differential equations (Q2025270) (← links)
- High-order combined multi-step scheme for solving forward backward stochastic differential equations (Q2028543) (← links)
- Discretization and machine learning approximation of BSDEs with a constraint on the gains-process (Q2031302) (← links)
- Stochastic ordering by \(g\)-expectations (Q2038280) (← links)
- Backward stochastic differential equations with no driving martingale, Markov processes and associated pseudo-partial differential equations. II: Decoupled mild solutions and examples (Q2042031) (← links)
- Reflected backward stochastic differential equation with rank-based data (Q2042035) (← links)
- A study of backward stochastic differential equation on a Riemannian manifold (Q2042810) (← links)
- Gradient convergence of deep learning-based numerical methods for BSDEs (Q2044106) (← links)
- Mean-field backward stochastic differential equations driven by fractional Brownian motion (Q2044792) (← links)
- Forcing the system by a drift (Q2049586) (← links)
- Multilevel Picard iterations for solving smooth semilinear parabolic heat equations (Q2063953) (← links)
- Strong solutions of forward-backward stochastic differential equations with measurable coefficients (Q2066956) (← links)
- Algorithms of data generation for deep learning and feedback design: a survey (Q2077720) (← links)
- Solvability of a class of mean-field BSDEs with quadratic growth (Q2081771) (← links)
- FBSDE based neural network algorithms for high-dimensional quasilinear parabolic PDEs (Q2083635) (← links)
- Solving BSDEs based on novel multi-step schemes and multilevel Monte Carlo (Q2088763) (← links)
- Solvability of infinite horizon McKean-Vlasov FBSDEs in mean field control problems and games (Q2096961) (← links)
- Parameter identification for portfolio optimization with a slow stochastic factor (Q2101109) (← links)
- Well-posedness of mean reflected BSDEs with non-Lipschitz coefficients (Q2105392) (← links)
- McKean Feynman-Kac probabilistic representations of non-linear partial differential equations (Q2107414) (← links)
- Backward stochastic differential equations driven by \(G\)-Brownian motion with uniformly continuous coefficients in \((y, z)\) (Q2116484) (← links)
- Neumann boundary problems for parabolic partial differential equations with divergence terms (Q2118854) (← links)
- A forward-backward probabilistic algorithm for the incompressible Navier-Stokes equations (Q2125000) (← links)
- Classical and weak solutions of the partial differential equations associated with a class of two-point boundary value problems (Q2126432) (← links)
- A Feynman-Kac based numerical method for the exit time probability of a class of transport problems (Q2132650) (← links)
- Kernel learning backward SDE filter for data assimilation (Q2133767) (← links)
- Gradient boosting-based numerical methods for high-dimensional backward stochastic differential equations (Q2141183) (← links)
- Backward propagation of chaos (Q2144343) (← links)
- A class of quadratic forward-backward stochastic differential equations (Q2147795) (← links)
- \(L^p\) solution of general mean-field BSDEs with continuous coefficients (Q2151504) (← links)
- Coupled FBSDEs with measurable coefficients and its application to parabolic PDEs (Q2154437) (← links)
- Path dependent Feynman-Kac formula for forward backward stochastic Volterra integral equations (Q2155507) (← links)
- Reflected BSDEs in non-convex domains (Q2159261) (← links)
- Convolutional neural network based simulation and analysis for backward stochastic partial differential equations (Q2159857) (← links)
- A regression-based Monte Carlo method to solve two-dimensional forward backward stochastic differential equations (Q2166927) (← links)
- Deep neural networks based temporal-difference methods for high-dimensional parabolic partial differential equations (Q2168314) (← links)
- Convergence of deep fictitious play for stochastic differential games (Q2170300) (← links)
- Weighted bounded mean oscillation applied to backward stochastic differential equations (Q2175336) (← links)
