Index

_

__add__() (Sample method), [1], [2] __call__() (Sample method), [1], [2] _ApproximateKernel (class in gpflux.sampling.kernel_with_feature_decomposition) _bases_concat() (in module gpflux.layers.basis_functions.fourier_features.quadrature.gaussian) (in module gpflux.layers.basis_functions.fourier_features.utils) _bases_cosine() (in module gpflux.layers.basis_functions.fourier_features.utils) _cholesky_with_jitter() (in module gpflux.layers.gp_layer) (in module gpflux.math) (in module gpflux.sampling.utils) _compute_bases() (FourierFeaturesBase method), [1] (QuadratureFourierFeatures method), [1], [2] (RandomFourierFeatures method), [1] (RandomFourierFeaturesCosine method), [1] _compute_constant() (FourierFeaturesBase method), [1] (QuadratureFourierFeatures method), [1], [2] (RandomFourierFeatures method), [1] (RandomFourierFeaturesCosine method), [1]

_construct_kernel() (in module gpflux.architectures.constant_input_dim_deep_gp) _convert_to_tensor_fn() (GPLayer method), [1], [2], [3] _efficient_sample_conditional_gaussian() (in module gpflux.sampling.sample) _efficient_sample_matheron_rule() (in module gpflux.sampling.sample) _evaluate_deep_gp() (DeepGP method), [1], [2] _evaluate_likelihood() (DeepGP method), [1], [2] _inference_latent_samples_and_loss() (LatentVariableLayer method), [1] _inference_posteriors() (LatentVariableLayer method), [1] _local_kls() (LatentVariableLayer method), [1] _make_distribution_fn() (GPLayer method), [1], [2], [3] _prediction_latent_samples() (LatentVariableLayer method), [1] _validate_dtype() (DeepGP static method), [1], [2] _validate_num_data() (DeepGP static method), [1], [2]

A

as_prediction_model() (DeepGP method), [1], [2]

as_training_model() (DeepGP method), [1], [2]

B

BayesianDenseLayer (class in gpflux.layers) (class in gpflux.layers.bayesian_dense_layer) build() (BayesianDenseLayer method), [1] (QuadratureFourierFeatures method), [1], [2] (RandomFourierFeaturesCosine method), [1]

build_constant_input_dim_deep_gp() (in module gpflux.architectures) (in module gpflux.architectures.constant_input_dim_deep_gp)

C

call() (BayesianDenseLayer method), [1] (DirectlyParameterizedNormalDiag method), [1] (FourierFeaturesBase method), [1] (GPLayer method), [1], [2], [3] (LatentVariableLayer method), [1] (LayerWithObservations method), [1], [2] (LikelihoodLayer method), [1], [2], [3] (LikelihoodLoss method) (NatGradWrapper method), [1] compositor (LatentVariableLayer attribute), [1] compute_A_inv_b() (in module gpflux.math) (in module gpflux.sampling.sample)

compute_output_shape() (FourierFeaturesBase method), [1] Config (class in gpflux.architectures) (class in gpflux.architectures.constant_input_dim_deep_gp) construct_basic_inducing_variables() (in module gpflux.architectures.constant_input_dim_deep_gp) (in module gpflux.helpers) construct_basic_kernel() (in module gpflux.architectures.constant_input_dim_deep_gp) (in module gpflux.helpers) construct_gp_layer() (in module gpflux.helpers) construct_mean_function() (in module gpflux.architectures.constant_input_dim_deep_gp) (in module gpflux.helpers)

D

DeepGP (class in gpflux.architectures.constant_input_dim_deep_gp) (class in gpflux.models) (class in gpflux.models.deep_gp) default_model_class (DeepGP attribute), [1], [2]

DirectlyParameterizedNormalDiag (class in gpflux.encoders) (class in gpflux.encoders.directly_parameterized_encoder) draw_conditional_sample() (in module gpflux.sampling.sample) (in module gpflux.sampling.utils)

E

efficient_sample (in module gpflux.layers.gp_layer) (in module gpflux.sampling) (in module gpflux.sampling.sample)

elbo() (DeepGP method), [1], [2] encoder (LatentVariableLayer attribute), [1] EncoderInitializationError, [1] Event (class in gpflux.experiment_support.tensorboard)

F

f_layers (DeepGP attribute), [1], [2] feature_coefficients (KernelWithFeatureDecomposition property), [1], [2] feature_functions (KernelWithFeatureDecomposition property), [1], [2]

FourierFeaturesBase (class in gpflux.layers.basis_functions.fourier_features.base) (class in gpflux.layers.basis_functions.fourier_features.quadrature.gaussian) full_cov (GPLayer attribute), [1], [2], [3] full_output_cov (GPLayer attribute), [1], [2], [3]

G

get_config() (FourierFeaturesBase method), [1] gpflux module, [1] gpflux.architectures module gpflux.architectures.constant_input_dim_deep_gp module gpflux.callbacks module gpflux.encoders module gpflux.encoders.directly_parameterized_encoder module gpflux.exceptions module gpflux.experiment_support module gpflux.experiment_support.ci_utils module gpflux.experiment_support.tensorboard module gpflux.helpers module gpflux.layers module gpflux.layers.basis_functions module gpflux.layers.basis_functions.fourier_features module gpflux.layers.basis_functions.fourier_features.base module gpflux.layers.basis_functions.fourier_features.quadrature module gpflux.layers.basis_functions.fourier_features.quadrature.gaussian module gpflux.layers.basis_functions.fourier_features.random module gpflux.layers.basis_functions.fourier_features.utils module gpflux.layers.bayesian_dense_layer module

gpflux.layers.gp_layer module gpflux.layers.latent_variable_layer module gpflux.layers.likelihood_layer module gpflux.layers.trackable_layer module gpflux.losses module gpflux.math module gpflux.models module gpflux.models.deep_gp module gpflux.optimization module gpflux.optimization.keras_natgrad module gpflux.runtime_checks module gpflux.sampling module gpflux.sampling.kernel_with_feature_decomposition module gpflux.sampling.sample module gpflux.sampling.utils module gpflux.types module gpflux.version module GPLayer (class in gpflux.architectures.constant_input_dim_deep_gp) (class in gpflux.helpers) (class in gpflux.layers) (class in gpflux.layers.gp_layer) GPLayerIncompatibilityException, [1], [2]

I

inner_layer_qsqrt_factor (Config attribute), [1]

is_continuous_integration() (in module gpflux.experiment_support.ci_utils)

K

K() (_ApproximateKernel method) K_diag() (_ApproximateKernel method) KernelWithFeatureDecomposition (class in gpflux.sampling) (class in gpflux.sampling.kernel_with_feature_decomposition) (class in gpflux.sampling.sample)

keywords_to_monitor (TensorBoard attribute)

L

LatentVariableLayer (class in gpflux.layers) (class in gpflux.layers.latent_variable_layer) LayerWithObservations (class in gpflux.layers) (class in gpflux.layers.latent_variable_layer) (class in gpflux.models.deep_gp) likelihood_layer (DeepGP attribute), [1], [2] likelihood_noise_variance (Config attribute), [1]

LikelihoodLayer (class in gpflux.architectures.constant_input_dim_deep_gp) (class in gpflux.layers) (class in gpflux.layers.likelihood_layer) (class in gpflux.models.deep_gp) LikelihoodLoss (class in gpflux.losses) LikelihoodOutputs (class in gpflux.layers.likelihood_layer) log_dir (TensorBoard attribute)

M

make_dataclass_from_class() (in module gpflux.helpers) means (DirectlyParameterizedNormalDiag attribute), [1] module gpflux, [1] gpflux.architectures gpflux.architectures.constant_input_dim_deep_gp gpflux.callbacks gpflux.encoders gpflux.encoders.directly_parameterized_encoder gpflux.exceptions gpflux.experiment_support gpflux.experiment_support.ci_utils gpflux.experiment_support.tensorboard gpflux.helpers gpflux.layers gpflux.layers.basis_functions gpflux.layers.basis_functions.fourier_features gpflux.layers.basis_functions.fourier_features.base gpflux.layers.basis_functions.fourier_features.quadrature gpflux.layers.basis_functions.fourier_features.quadrature.gaussian gpflux.layers.basis_functions.fourier_features.random gpflux.layers.basis_functions.fourier_features.utils gpflux.layers.bayesian_dense_layer gpflux.layers.gp_layer gpflux.layers.latent_variable_layer gpflux.layers.likelihood_layer gpflux.layers.trackable_layer gpflux.losses gpflux.math gpflux.models gpflux.models.deep_gp gpflux.optimization gpflux.optimization.keras_natgrad gpflux.runtime_checks gpflux.sampling gpflux.sampling.kernel_with_feature_decomposition gpflux.sampling.sample gpflux.sampling.utils gpflux.types gpflux.version

N

natgrad_layers (NatGradModel property), [1] NatGradModel (class in gpflux.optimization) (class in gpflux.optimization.keras_natgrad) NatGradWrapper (class in gpflux.optimization) (class in gpflux.optimization.keras_natgrad) notebook_list() (in module gpflux.experiment_support.ci_utils)

notebook_niter() (in module gpflux.experiment_support.ci_utils) notebook_range() (in module gpflux.experiment_support.ci_utils) num_data (DeepGP attribute), [1], [2] (GPLayer attribute), [1], [2], [3] num_inducing (Config attribute), [1] num_samples (GPLayer attribute), [1], [2], [3]

O

ObservationType (in module gpflux.layers.latent_variable_layer) (in module gpflux.types) on_epoch_end() (TensorBoard method)

on_train_batch_end() (TensorBoard method) optimizer (NatGradModel property), [1] OrthogonalRandomFeatures (class in gpflux.layers.basis_functions.fourier_features) (class in gpflux.layers.basis_functions.fourier_features.random)

P

predict() (GPLayer method), [1], [2], [3] predict_f() (DeepGP method), [1], [2] predict_samples() (BayesianDenseLayer method), [1]

prior (LatentVariableLayer attribute), [1] prior_kl() (BayesianDenseLayer method), [1] (GPLayer method), [1], [2], [3]

Q

q_mu (GPLayer attribute), [1], [2], [3] q_sqrt (GPLayer attribute), [1], [2], [3]

QuadratureFourierFeatures (class in gpflux.layers.basis_functions.fourier_features) (class in gpflux.layers.basis_functions.fourier_features.quadrature) (class in gpflux.layers.basis_functions.fourier_features.quadrature.gaussian)

R

RandomFourierFeatures (class in gpflux.layers.basis_functions.fourier_features) (class in gpflux.layers.basis_functions.fourier_features.random)

RandomFourierFeaturesCosine (class in gpflux.layers.basis_functions.fourier_features) (class in gpflux.layers.basis_functions.fourier_features.random)

S

Sample (class in gpflux.layers.gp_layer) (class in gpflux.models.deep_gp) (class in gpflux.sampling.sample) sample() (GPLayer method), [1], [2], [3] set_model() (TensorBoard method)

ShapeType (in module gpflux.layers.basis_functions.fourier_features.base) (in module gpflux.layers.basis_functions.fourier_features.quadrature.gaussian) (in module gpflux.layers.bayesian_dense_layer) (in module gpflux.types) stds (DirectlyParameterizedNormalDiag attribute), [1]

T

TensorBoard (class in gpflux.callbacks) tensorboard_event_iterator() (in module gpflux.experiment_support.tensorboard) TrackableLayer (class in gpflux.encoders.directly_parameterized_encoder) (class in gpflux.layers) (class in gpflux.layers.bayesian_dense_layer) (class in gpflux.layers.latent_variable_layer) (class in gpflux.layers.likelihood_layer) (class in gpflux.layers.trackable_layer)

train_step() (NatGradModel method), [1]

U

unwrap_dist() (in module gpflux.layers.likelihood_layer) (in module gpflux.losses) (in module gpflux.types)

update_freq (TensorBoard attribute)

V

verify_compatibility() (in module gpflux.layers.gp_layer) (in module gpflux.runtime_checks)

W

whiten (Config attribute), [1] (GPLayer attribute), [1], [2], [3]

X

xavier_initialization_numpy() (in module gpflux.helpers) (in module gpflux.layers.bayesian_dense_layer)