gpLib.MinKernel

class gpLib.MinKernel(offset_prior: Prior | None = None, offset_constraint: Interval | None = None, **kwargs)

Min kernel (integrated Brownian motion)

\[k(x,x') \;=\; \min(x,x') + \text{offset}.\]

For numerical efficiency we use the identity

\[\min(x,x') \;=\; \tfrac12\!\bigl(|x| + |x'| - |x-x'|\bigr).\]

The underlying covariance is that of a continuous-time Brownian motion (discrete-time Gaussian random walk).

Variables:

offset (torch.Tensor) – Non-negative constant added to all entries.