tfp.experimental.distributions.marginal_fns.make_eigh_marginal_fn

Make an eigenvalue decomposition-based marginal_fn.

tfp.experimental.distributions.marginal_fns.make_eigh_marginal_fn(
    tol=1e-06, name='EigHMarginalFn'
)

For use with GaussianProcess classes.

A matrix square root is produced using an eigendecomposition. Eigenvalues are forced to be above a tolerance, to ensure positive-definiteness.

Args
`tol`	Scalar float `Tensor`. Eigenvalues below `tol` are raised to `tol`.
`name`	Python `str` name prefixed to Ops created by this function. Default value: 'EigHMarginalFn'.

Returns
`marginal_function`	A function that can be used with the `marginal_fn` argument to `GaussianProcess`.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2023-11-21 UTC.

tfp.experimental.distributions.marginal_fns.make_eigh_marginal_fn Stay organized with collections Save and categorize content based on your preferences.