Stochastic PINNs - merging PINNs and stochastic differential equations

Prelegent(ci)

Paweł Przybyłowicz

Afiliacja

AGH Kraków

Język referatu

angielski

Termin

16 kwietnia 2026 10:15

Pokój

p. 4070

Seminarium

Seminarium Zakładu Analizy Numerycznej

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The talk presents a new methodology, called stochastic PINNs (StPINNs), for approximating sample paths of stochastic differential equations (SDEs) using artificial neural networks. The method is based on a Doss–Sussman transformation of the initial SDE into a random ordinary differential equation (RODE). The approach targets pathwise accuracy, highlights practical training strategies, and is demonstrated on benchmark SDE models. The talk is based on: https://arxiv.org/abs/2512.14258

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