mlsanityData to 7 Oct 2026

Convergence of a Deep BSDE solver with jumps

arXiv 2501.09727 ↗First posted 16 Jan 2025math.PR cs.NA math.NAcited by 4

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Abstract (arXiv)

We study the error arising in the numerical approximation of FBSDEs and related PIDEs by means of a deep learning-based method. Our results focus on decoupled FBSDEs with jumps and extend the seminal work of HAn and Long (2020) analyzing the numerical error of the deep BSDE solver proposed in E et al. (2017). We provide a priori and a posteriori error estimates for the finite and infinite activity case.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Jan 2025.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.

  1. 2025A deep solver for backward stochastic Volterra integral equationscited by 1
  2. 2026INEUS: Iterative Neural Solver for High-Dimensional PIDEscited by 0
  3. 2026A Posteriori Error Analysis for Decoupled Neural Approximations of Fully Coupled FBSDEs with Control Mismatchcited by 0
  4. 2026Deep Learning for Reflected BSDEs: Regularization and Error Analysiscited by 0