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18 changes: 11 additions & 7 deletions src/kernels/gibbskernel.jl
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"""
@doc raw"""
GibbsKernel(; lengthscale)

# Definition
Gibbs Kernel with lengthscale function `lengthscale`.

The Gibbs kernel is non-stationary generalisation of the squared exponential
The Gibbs kernel is a non-stationary generalisation of the squared exponential
kernel. The lengthscale parameter ``l`` becomes a function of
position ``l(x)``.

For a constant function``l(x) = c``, one recovers the standard squared exponential kernel
with lengthscale `c`.
# Definition

For inputs ``x, x'``, the Gibbs kernel with lengthscale function ``l(\cdot)``
is defined as
```math
k(x, y; l) = \\sqrt{ \\left(\\frac{2 l(x) l(y)}{l(x)^2 + l(y)^2} \\right) }
\\quad \\rm{exp} \\left( - \\frac{(x - y)^2}{l(x)^2 + l(y)^2} \\right)
k(x, x'; l) = \sqrt{\left(\frac{2 l(x) l(x')}{l(x)^2 + l(x')^2}\right)}
\quad \exp{\left(-\frac{(x - x')^2}{l(x)^2 + l(x')^2}\right)}.
```

For a constant function ``l \equiv c``, one recovers the [`SqExponentialKernel`](@ref)
with lengthscale `c`.

# References

Mark N. Gibbs. "Bayesian Gaussian Processes for Regression and Classication." PhD thesis, 1997
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