Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems
von Nikolas Nüsken, Lorenz Richter
Jahr:
2021
Publikation:
eprint arXiv:2112.03749
Abstrakt:
Solving high-dimensional partial differential equations is a recurrent challenge in economics, science and engineering. In recent years, a great number of computational approaches have been developed, most of them relying on a combination of Monte Carlo sampling and deep learning based approximation.
Link:
Read the paperAdditional Information
Brief introduction of the dida co-author(s) and relevance for dida's ML developments.
Dr. Lorenz Richter
Aus der Stochastik und Numerik kommend (FU Berlin), beschäftigt sich der Mathematiker seit einigen Jahren mit Deep-Learning-Algorithmen. Neben seinem Faible für die Theorie hat er in den letzten 10 Jahren diverse Data Science-Probleme praktisch gelöst. Lorenz leitet das Machine-Learning-Team.