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Boundary-safe PINNs extension

3 pagesPublished: February 16, 2023


The goal of this work is to solve a nonlinear parabolic PDE problem that arise in the financial world by means of the so called PINNs methodology. We propose a novel treat- ment of the boundary conditions that allows us to avoid, as far as possible, the heuristic choice of the weights for the contributions of the boundary addends of the loss function that come from the boundary conditions.

Keyphrases: Black-Scholes model, boundary conditions, deep learning, non-linear PDEs, Physics-informed neural networks

In: Alvaro Leitao and Lucía Ramos (editors). Proceedings of V XoveTIC Conference. XoveTIC 2022, vol 14, pages 142--144

BibTeX entry
  author    = {Joel P. Villarino and Jos\textbackslash{}'e A. Garc\textbackslash{}'ia Rodr\textbackslash{}'iguez and \textbackslash{}'Alvaro Leitao},
  title     = {Boundary-safe PINNs extension},
  booktitle = {Proceedings of V XoveTIC Conference. XoveTIC 2022},
  editor    = {Alvaro Leitao and Luc\textbackslash{}'ia Ramos},
  series    = {Kalpa Publications in Computing},
  volume    = {14},
  pages     = {142--144},
  year      = {2023},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2515-1762},
  url       = {},
  doi       = {10.29007/rddw}}
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