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Physics Informed Neural Networks is a numerical method which uses neural networks to approximate solutions of partial differential equations.
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On maximal regularity estimates for discontinuous Galerkin time-discrete methods
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Variational physics informed neural networks: the role of quadratures and test functions
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A deep learning approach to nonconvex energy minimization for martensitic phase transitions
X. Chen, P. Rosakis, Z. Wu, and Z. Zhang · 2022
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