Probabilistic numerics and uncertainty in computations

  title={Probabilistic numerics and uncertainty in computations},
  author={Philipp Hennig and Michael A. Osborne and Mark A. Girolami},
  journal={Proceedings. Mathematical, Physical, and Engineering Sciences / The Royal Society},
We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions… 

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