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Solving high-dimensional Hamilton–Jacobi–Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space

Crossref DOI link: https://doi.org/10.1007/s42985-021-00102-x

Published Online: 2021-06-21

Published Print: 2021-08

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Nüsken, Nikolas

Richter, Lorenz http://orcid.org/0000-0001-5028-5639
Funding

Funding for this research was provided by:

Deutsche Forschungsgemeinschaft (CRC 1114, project number 235221301)

Deutsche Forschungsgemeinschaft (CRC 1114, project number 235221301)
License Information

Text and Data Mining valid from 2021-06-21

Version of Record valid from 2021-06-21
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Article History

Received: 18 June 2020

Accepted: 16 May 2021

First Online: 21 June 2021

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