WhiteNoiseKernel

class pmrf.discrepancy_models.kernels.WhiteNoiseKernel(variance: Any = 1.0, *, name: str | None = None)

Bases: CovarianceKernel

Kernel representing independent Gaussian noise.

Variables:

variance (prx.Parameter) – Noise variance level (default 1.0).

__call__(x1, x2, key=None)

Evaluate the kernel between two points.

Parameters:

• x1 (jnp.ndarray) – First input point.

• x2 (jnp.ndarray) – Second input point.

• key (jax.random.PRNGKey, optional) – Random key for stochastic kernels.

Returns:

Kernel covariance scalar.

Return type:

jnp.ndarray

variance: Parameter = 1.0