• Corpus ID: 203610462

Non-Gaussian processes and neural networks at finite widths

  title={Non-Gaussian processes and neural networks at finite widths},
  author={Sho Yaida},
  booktitle={Mathematical and Scientific Machine Learning},
  • Sho Yaida
  • Published in
    Mathematical and Scientific…
    25 September 2019
  • Computer Science
Gaussian processes are ubiquitous in nature and engineering. A case in point is a class of neural networks in the infinite-width limit, whose priors correspond to Gaussian processes. Here we perturbatively extend this correspondence to finite-width neural networks, yielding non-Gaussian processes as priors. The methodology developed herein allows us to track the flow of preactivation distributions by progressively integrating out random variables from lower to higher layers, reminiscent of… 

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