tfp.experimental.distributions.marginal_fns.make_cholesky_like_marginal_fn

Use a Cholesky-like function for GaussianProcess marginal_fn.

tfp.experimental.distributions.marginal_fns.make_cholesky_like_marginal_fn(
    cholesky_like, name='CholeskyLikeMarginalFn'
)

For use with "Cholesky-like" lower-triangular factorizations (LL^T). See make_backoff_cholesky for one way to create such functions.

Args
`cholesky_like`	A callable with the same signature as `tf.linalg.cholesky.`
`name`	Python `str` name prefixed to Ops created by this function. Default value: 'CholeskyLikeMarginalFn'.

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.

Args