Learning stable and predictive structures in kinetic systems

@article{Pfister2019LearningSA,
  title={Learning stable and predictive structures in kinetic systems},
  author={Niklas Pfister and S. Bauer and J. Peters},
  journal={Proceedings of the National Academy of Sciences},
  year={2019},
  volume={116},
  pages={25405 - 25411}
}
  • Niklas Pfister, S. Bauer, J. Peters
  • Published 2019
  • Mathematics, Computer Science, Medicine
  • Proceedings of the National Academy of Sciences
  • Significance Many real-world systems can be described by a set of differential equations. Knowing these equations allows researchers to predict the system’s behavior under interventions, such as manipulations of initial or environmental conditions. For many complex systems, the differential equations are unknown. Deriving them by hand is infeasible for large systems, and data science is used to learn them from observational data. Existing techniques yield models that predict the observational… CONTINUE READING
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