Python Module Index

e | f | i | j | n | p | s | u | w


	e
	`jaxns.experimental`
	`jaxns.experimental.evidence_maximisation`
	`jaxns.experimental.global_optimisation`
	`jaxns.experimental.public`
	`jaxns.experimental.solvers`
	`jaxns.experimental.solvers.ad_utils`
	`jaxns.experimental.solvers.cg`
	`jaxns.experimental.solvers.gauss_newton_cg`
	`jaxns.experimental.solvers.test_cg`

	f
	`jaxns.framework`
	`jaxns.framework.abc`
	`jaxns.framework.bases`
	`jaxns.framework.context`
	`jaxns.framework.jaxify`
	`jaxns.framework.model`
	`jaxns.framework.ops`
	`jaxns.framework.prior`
	`jaxns.framework.special_priors`
	`jaxns.framework.wrapped_tfp_distribution`

	i
	`jaxns.internals`
	`jaxns.internals.constraint_bijections`
	`jaxns.internals.cumulative_ops`
	`jaxns.internals.interp_utils`
	`jaxns.internals.linalg`
	`jaxns.internals.log_semiring`
	`jaxns.internals.logging`
	`jaxns.internals.maps`
	`jaxns.internals.mixed_precision`
	`jaxns.internals.namedtuple_utils`
	`jaxns.internals.prefix_sum`
	`jaxns.internals.pytree_utils`
	`jaxns.internals.random`
	`jaxns.internals.shapes`
	`jaxns.internals.shrinkage_statistics`
	`jaxns.internals.stats`
	`jaxns.internals.tree_structure`
	`jaxns.internals.types`

	j
	`jaxns`	Nested sampling with JAX.

	n
	`jaxns.nested_samplers`
	`jaxns.nested_samplers.abc`
	`jaxns.nested_samplers.common`
	`jaxns.nested_samplers.common.initialisation`
	`jaxns.nested_samplers.common.termination`
	`jaxns.nested_samplers.common.types`
	`jaxns.nested_samplers.common.uniform_sample`
	`jaxns.nested_samplers.sharded`
	`jaxns.nested_samplers.sharded.sharded_static`

	p
	`jaxns.plotting`
	`jaxns.public`

	s
	`jaxns.samplers`
	`jaxns.samplers.abc`
	`jaxns.samplers.bases`
	`jaxns.samplers.multi_ellipsoid`
	`jaxns.samplers.multi_ellipsoid.em_gmm`
	`jaxns.samplers.multi_ellipsoid.multi_ellipsoid_utils`
	`jaxns.samplers.multi_ellipsoidal_samplers`
	`jaxns.samplers.multi_slice_sampler`
	`jaxns.samplers.uni_slice_sampler`
	`jaxns.samplers.uniform_samplers`

	u
	`jaxns.utils`

	w
	`jaxns.warnings`