Automatic physical inference with information maximising neural networks

@article{Charnock2018AutomaticPI,
  title={Automatic physical inference with information maximising neural networks},
  author={Tom Charnock and Guilhem Lavaux and Benjamin D. Wandelt},
  journal={Physical Review D},
  year={2018},
  volume={97}
}
  • Tom Charnock, Guilhem Lavaux, Benjamin D. Wandelt
  • Published 2018
  • Physics
  • Physical Review D
  • Compressing large data sets to a manageable number of summaries that are informative about the underlying parameters vastly simplifies both frequentist and Bayesian inference. When only simulations are available, these summaries are typically chosen heuristically, so they may inadvertently miss important information. We introduce a simulation-based machine learning technique that trains artificial neural networks to find non-linear functionals of data that maximise Fisher information… CONTINUE READING

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