ZeroKernel

class pmrf.covariance_kernels.ZeroKernel

Bases: AbstractCovarianceKernel

Kernel that always evaluates to zero.

Useful for masking out cross-covariances in multi-output models to enforce strict independence between tasks.

__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