Temporal difference learning for high-dimensional PIDEs with jumps (Q6575343)

scientific article; zbMATH DE number 7883829

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English	Temporal difference learning for high-dimensional PIDEs with jumps	scientific article; zbMATH DE number 7883829

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instance of

scholarly article

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title

Temporal difference learning for high-dimensional PIDEs with jumps (English)

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SIAM Journal on Scientific Computing

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publication date

19 July 2024

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zbMATH Keywords

Lévy motion

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reinforcement learning

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partial integro-differential equation

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temporal difference learning

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MaRDI profile type

Publication

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cites work

A nonlinear partial integro-differential equation from mathematical finance

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A Finite Difference Scheme for Option Pricing in Jump Diffusion and Exponential Lévy Models

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Scientific machine learning through physics-informed neural networks: where we are and what's next

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Backward stochastic differential equations with jumps and their actuarial and financial applications. BSDEs with jumps

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Q2930843

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The Deep Ritz Method: a deep learning-based numerical algorithm for solving variational problems

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A system of non-local parabolic PDE and application to option pricing

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Optimal error estimates of two mixed finite element methods for parabolic integro-differential equations with nonsmooth initial data

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Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations

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Solving high-dimensional partial differential equations using deep learning

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Non-local partial differential equations for engineering and biology. Mathematical modeling and analysis

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\textit{hp}-VPINNs: variational physics-informed neural networks with domain decomposition

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A Second-order Finite Difference Method for Option Pricing Under Jump-diffusion Models

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Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions

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DeepXDE: A Deep Learning Library for Solving Differential Equations

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MIM: a deep mixed residual method for solving high-order partial differential equations

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Self-adaptive physics-informed neural networks

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Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations

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A finite elements approach for spread contract valuation via associated two-dimensional PIDE

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Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

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DGM: a deep learning algorithm for solving partial differential equations

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Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks

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Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems

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Weak adversarial networks for high-dimensional partial differential equations

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Deep neural networks based temporal-difference methods for high-dimensional parabolic partial differential equations

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Identifiers

zbMATH Open document ID

1545.65044

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Mathematics Subject Classification ID

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Mathematics(1 entry)

mardi Publication:6575343