Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems

@article{Tanyu2022DeepLM,
  title={Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems},
  author={Derick Nganyu Tanyu and Jianfeng Ning and Tom Freudenberg and Nick Heilenk{\"o}tter and Andreas Rademacher and Uwe Iben and Peter Maass},
  journal={ArXiv},
  year={2022},
  volume={abs/2212.03130}
}
Recent years have witnessed a growth in mathematics for deep learning—which seeks a deeper understanding of the concepts of deep learning with mathematics, and explores how to make it more robust—and deep learning for mathematics, where deep learning algorithms are used to solve problems in mathematics. The latter has popularised the field of scientific machine learning where deep learning is applied to problems in scientific computing. Specifically, more and more neural network architectures… 
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3 Citations

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