A deep branching solver for fully nonlinear partial differential equations
We present a multidimensional deep learning implementation of a stochastic branching algorithm for the numerical solution of fully nonlinear PDEs. This approach is designed to tackle functional nonlinearities involving gradient terms of any orders, by combining the use of neural networks with a Mont...
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Main Authors: | Nguwi, Jiang Yu, Penent, Guillaume, Privault, Nicolas |
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Other Authors: | School of Physical and Mathematical Sciences |
Format: | Article |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/178069 |
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Institution: | Nanyang Technological University |
Language: | English |
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