Using Gaussian processes we can approximate the weight space integral analytically, so that only a small number of hyperparameters need be integrated over by ...

Using Gaussian processes we can approximate the weight space integral analytically, so that only a small number of hyperparameters need be integrated over by ...

Nov 1, 2024 · Copy. Barber, David and Williams, Christopher K. I. (1997). Gaussian processes for Bayesian classification via Hybrid Monte Carlo.

We provide a Bayesian treatment, integrating over uncertainty in y and in the parameters that control the Gaussian process prior; the necessary integration over ...

SUMMARY. Hybrid Monte Carlo (HMC) is often the method of choice for computing Bayesian integrals that are not analytically tractable.

Barber and C.K.I Williams, “Gaussian Processes for Bayesian. Classification via Hybrid Monte Carlo,” M.C. Mozer, M.I. Jordan, and T. Petsche, eds., Advances ...

A Bayesian treatment is provided, integrating over uncertainty in y and in the parameters that control the Gaussian process prior the necessary integration ...

Sep 18, 2024 · Gaussian processes are a natural way of defining prior distributions over functions of one or more input variables.

Oct 6, 2024 · We propose a novel method for quantifying failure probabilities of complex computer simulations when the computation budget restricts evaluations of the ...

SUMMARY. Hybrid Monte Carlo (HMC) is often the method of choice for computing Bayesian integrals that are not analytically tractable.