Module: tfp.experimental.distributions.marginal_fns
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Experimental functions to use as marginals for GaussianProcess(es).
Modules
mvn_linear_operator module: Multivariate Normal distribution classes.
ps module: Operations that use static values when possible.
tfp_custom_gradient module: TF and JAX compatible custom gradients.
Functions
make_backoff_cholesky(...): Make a function that tries Cholesky then the user-specified function.
make_cholesky_like_marginal_fn(...): Use a Cholesky-like function for GaussianProcess marginal_fn.
make_eigh_marginal_fn(...): Make an eigenvalue decomposition-based marginal_fn.
retrying_cholesky(...): Computes a modified Cholesky decomposition for a batch of square matrices.
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Last updated 2023-11-21 UTC.
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