Probabilistic neural network-based 2D travel-time tomography

@article{Earp2020ProbabilisticNN,
  title={Probabilistic neural network-based 2D travel-time tomography},
  author={Stephanie Earp and Andrew Curtis},
  journal={Neural Computing and Applications},
  year={2020},
  pages={1 - 19}
}
  • S. Earp, A. Curtis
  • Published 27 June 2019
  • Mathematics
  • Neural Computing and Applications
Travel-time tomography for the velocity structure of a medium is a highly nonlinear and nonunique inverse problem. Monte Carlo methods are becoming increasingly common choices to provide probabilistic solutions to tomographic problems but those methods are computationally expensive. Neural networks can often be used to solve highly nonlinear problems at a much lower computational cost when multiple inversions are needed from similar data types. We present the first method to perform fully… 

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