Corpus ID: 218673725

SciANN: A Keras wrapper for scientific computations and physics-informed deep learning using artificial neural networks

@article{Haghighat2020SciANNAK,
  title={SciANN: A Keras wrapper for scientific computations and physics-informed deep learning using artificial neural networks},
  author={E. Haghighat and R. Juanes},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.08803}
}
In this paper, we introduce SciANN, a Python package for scientific computing and physicsinformed deep learning using artificial neural networks. SciANN uses the widely used deeplearning packages Tensorflow and Keras to build deep neural networks and optimization models, thus inheriting many of Keras’s functionalities, such as batch optimization and model reuse for transfer learning. SciANN is designed to abstract neural network construction for scientific computations and solution and… Expand
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