Derives a Riccati-free coupled FBSDE system for mean-field Stackelberg games with random coefficients via extended Lagrange multipliers and proposes a Deep FBSDE Picard Solver with neural augmented Lagrangian for numerical solution.
Solving high-dimensional partial differen- tial equations using deep learning
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The Twisted-Path Particle Filter parameterizes twisting functions via neural networks and optimizes them against a path-measure KL divergence to improve continuous-time particle filtering.
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Stochastic Mean-Field LQ Stackelberg Differential Games with Random Coefficients: Theory and a Deep FBSDE Picard Solver
Derives a Riccati-free coupled FBSDE system for mean-field Stackelberg games with random coefficients via extended Lagrange multipliers and proposes a Deep FBSDE Picard Solver with neural augmented Lagrangian for numerical solution.
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Guidance for twisted particle filter: a continuous-time perspective
The Twisted-Path Particle Filter parameterizes twisting functions via neural networks and optimizes them against a path-measure KL divergence to improve continuous-time particle filtering.