Student-t Processes as Alternatives to Gaussian Processes

  title={Student-t Processes as Alternatives to Gaussian Processes},
  author={Amar Shah and Andrew Gordon Wilson and Zoubin Ghahramani},
We investigate the Student-t process as an alternative to the Gaussian process as a nonparametric prior over functions. We derive closed form expressions for the marginal likelihood and predictive distribution of a Student-t process, by integrating away an inverse Wishart process prior over the covariance kernel of a Gaussian process model. We show surprising equivalences between different hierarchical Gaussian process models leading to Student-t processes, and derive a new sampling scheme for… CONTINUE READING
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