MXFusion
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Installation
Design Overview
Model Definition
Inference
PPCA
CIPs
API Reference
mxfusion
mxfusion.components
mxfusion.components.distributions
mxfusion.components.distributions.categorical
mxfusion.components.distributions.distribution
mxfusion.components.distributions.normal
mxfusion.components.distributions.pointmass
mxfusion.components.distributions.random_gen
mxfusion.components.distributions.univariate
mxfusion.components.distributions.gp
mxfusion.components.distributions.gp.gp
mxfusion.components.distributions.gp.cond_gp
mxfusion.components.distributions.gp.kernels
mxfusion.components.distributions.gp.kernels.add_kernel
mxfusion.components.distributions.gp.kernels.kernel
mxfusion.components.distributions.gp.kernels.linear
mxfusion.components.distributions.gp.kernels.rbf
mxfusion.components.distributions.gp.kernels.static
mxfusion.components.distributions.gp.kernels.stationary
mxfusion.components.functions
mxfusion.components.functions.function_evaluation
mxfusion.components.functions.gluon_func_eval
mxfusion.components.functions.mxfusion_gluon_function
mxfusion.components.modules
mxfusion.components.modules.module
mxfusion.components.variables
mxfusion.components.variables.runtime_variable
mxfusion.components.variables.var_trans
mxfusion.components.variables.variable
mxfusion.components.factor
mxfusion.components.model_component
mxfusion.models
mxfusion.models.factor_graph
mxfusion.models.model
mxfusion.models.posterior
mxfusion.inference
mxfusion.inference.batch_loop
mxfusion.inference.forward_sampling
mxfusion.inference.grad_based_inference
mxfusion.inference.grad_loop
mxfusion.inference.inference_alg
mxfusion.inference.inference_parameters
mxfusion.inference.inference
mxfusion.inference.map
mxfusion.inference.meanfield
mxfusion.inference.minibatch_loop
mxfusion.inference.variational
mxfusion.util
mxfusion.util.customop
mxfusion.util.graph_serialization
mxfusion.util.inference
mxfusion.util.testutils
mxfusion.util.util
Tutorials
Introduction (through Probabilistic PCA)
Bayesian Neural Network Classification
Bayesian Neural Network Regression
Variational Auto-Encoder
Writing your own Distribution
MXFusion
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Index
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B
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C
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D
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E
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F
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H
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I
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K
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M
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N
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O
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P
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R
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S
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T
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U
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V
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W
A
add() (mxfusion.components.distributions.gp.kernels.kernel.Kernel method)
add_mxnet_params() (in module mxfusion.util.util)
add_sample_dimension() (in module mxfusion.components.variables.runtime_variable)
add_sample_dimension_arrays() (in module mxfusion.components.variables.runtime_variable)
AddKernel (class in mxfusion.components.distributions.gp.kernels.add_kernel)
as_samples() (in module mxfusion.components.variables.runtime_variable)
assign_factor() (mxfusion.components.variables.variable.Variable method)
B
backward() (mxfusion.util.customop.BroadcastToWithSamplesOp method)
BatchInferenceLoop (class in mxfusion.inference.batch_loop)
Bias (class in mxfusion.components.distributions.gp.kernels.static)
block_variables (mxfusion.components.functions.gluon_func_eval.GluonFunctionEvaluation attribute)
broadcast_to_w_samples() (in module mxfusion.util.customop)
BroadcastToWithSamplesOp (class in mxfusion.util.customop)
BroadcastToWithSamplesOpProp (class in mxfusion.util.customop)
C
Categorical (class in mxfusion.components.distributions.categorical)
CategoricalDrawSamplesDecorator (class in mxfusion.components.distributions.categorical)
CategoricalLogPDFDecorator (class in mxfusion.components.distributions.categorical)
clone() (mxfusion.models.factor_graph.FactorGraph method)
collect_internal_parameters() (mxfusion.components.functions.mxfusion_gluon_function.MXFusionGluonFunction method)
collect_params() (mxfusion.components.functions.mxfusion_gluon_function.MXFusionGluonFunction method)
CombinationKernel (class in mxfusion.components.distributions.gp.kernels.kernel)
components (mxfusion.models.factor_graph.FactorGraph attribute)
components_graph (mxfusion.models.factor_graph.FactorGraph attribute)
compute() (mxfusion.inference.forward_sampling.ForwardSamplingAlgorithm method)
(mxfusion.inference.inference_alg.InferenceAlgorithm method)
(mxfusion.inference.map.MAP method)
(mxfusion.inference.variational.StochasticVariationalInference method)
compute_log_prob() (mxfusion.models.factor_graph.FactorGraph method)
ConditionalGaussianProcess (class in mxfusion.components.distributions.gp.cond_gp)
ConditionalGaussianProcessDrawSamplesDecorator (class in mxfusion.components.distributions.gp.cond_gp)
ConditionalGaussianProcessLogPDFDecorator (class in mxfusion.components.distributions.gp.cond_gp)
constant (mxfusion.components.variables.variable.Variable attribute)
CONSTANT (mxfusion.components.variables.variable.VariableType attribute)
constants (mxfusion.inference.inference_parameters.InferenceParameters attribute)
create_constant_from_values() (in module mxfusion.util.util)
create_executor() (mxfusion.inference.grad_based_inference.GradBasedInference method)
(mxfusion.inference.inference.Inference method)
(mxfusion.inference.inference_alg.InferenceAlgorithm method)
create_Gaussian_meanfield() (in module mxfusion.inference.meanfield)
create_operator() (mxfusion.util.customop.BroadcastToWithSamplesOpProp method)
create_posterior() (mxfusion.inference.map.MAP static method)
create_variable() (mxfusion.components.modules.module.Module method)
create_variables_with_names() (in module mxfusion.util.util)
D
default() (mxfusion.util.graph_serialization.ModelComponentEncoder method)
define_variable() (mxfusion.components.distributions.categorical.Categorical static method)
(mxfusion.components.distributions.distribution.Distribution static method)
(mxfusion.components.distributions.gp.cond_gp.ConditionalGaussianProcess static method)
(mxfusion.components.distributions.gp.gp.GaussianProcess static method)
(mxfusion.components.distributions.normal.MultivariateNormal static method)
(mxfusion.components.distributions.normal.Normal static method)
(mxfusion.components.distributions.pointmass.PointMass static method)
discover_shape_constants() (in module mxfusion.util.inference)
display_str() (mxfusion.components.variables.variable.Variable method)
Distribution (class in mxfusion.components.distributions.distribution)
distributions (mxfusion.models.factor_graph.FactorGraph attribute)
DotProduct (class in mxfusion.util.testutils)
draw_samples() (mxfusion.components.distributions.categorical.Categorical method)
(mxfusion.components.distributions.distribution.Distribution method)
(mxfusion.components.distributions.gp.cond_gp.ConditionalGaussianProcess method)
(mxfusion.components.distributions.gp.gp.GaussianProcess method)
(mxfusion.components.distributions.normal.MultivariateNormal method)
(mxfusion.components.distributions.normal.Normal method)
(mxfusion.components.distributions.pointmass.PointMass method)
(mxfusion.models.factor_graph.FactorGraph method)
DrawSamplesDecorator (class in mxfusion.components.distributions.distribution)
E
eval() (mxfusion.components.functions.function_evaluation.FunctionEvaluation method)
(mxfusion.components.functions.gluon_func_eval.GluonFunctionEvaluation method)
expectation() (in module mxfusion.components.variables.runtime_variable)
extract_distribution_of() (mxfusion.models.factor_graph.FactorGraph method)
F
Factor (class in mxfusion.components.factor)
factor (mxfusion.components.variables.variable.Variable attribute)
FactorGraph (class in mxfusion.models.factor_graph)
fetch_parameters() (mxfusion.components.distributions.gp.kernels.kernel.Kernel method)
fetch_runtime_inputs() (mxfusion.components.factor.Factor method)
fetch_runtime_outputs() (mxfusion.components.factor.Factor method)
forward() (mxfusion.util.customop.BroadcastToWithSamplesOp method)
ForwardSampling (class in mxfusion.inference.forward_sampling)
ForwardSamplingAlgorithm (class in mxfusion.inference.forward_sampling)
FunctionEvaluation (class in mxfusion.components.functions.function_evaluation)
FunctionEvaluationDecorator (class in mxfusion.components.functions.function_evaluation)
functions (mxfusion.models.factor_graph.FactorGraph attribute)
FUNCVAR (mxfusion.components.variables.variable.VariableType attribute)
G
GaussianProcess (class in mxfusion.components.distributions.gp.gp)
GaussianProcessDrawSamplesDecorator (class in mxfusion.components.distributions.gp.gp)
GaussianProcessLogPDFDecorator (class in mxfusion.components.distributions.gp.gp)
generate_executor() (mxfusion.inference.inference.TransferInference method)
get_constants() (mxfusion.models.factor_graph.FactorGraph method)
get_latent_variables() (mxfusion.models.model.Model method)
get_num_samples() (in module mxfusion.components.variables.runtime_variable)
get_parameters() (mxfusion.models.factor_graph.FactorGraph method)
GluonFunctionEvaluation (class in mxfusion.components.functions.gluon_func_eval)
GradBasedInference (class in mxfusion.inference.grad_based_inference)
GradLoop (class in mxfusion.inference.grad_loop)
graph (mxfusion.components.model_component.ModelComponent attribute)
graphs (mxfusion.inference.inference.Inference attribute)
(mxfusion.inference.inference_alg.InferenceAlgorithm attribute)
H
hybrid_forward() (mxfusion.inference.inference_alg.ObjectiveBlock method)
(mxfusion.util.testutils.DotProduct method)
(mxfusion.util.testutils.TestBlock method)
I
infer_shape() (mxfusion.util.customop.BroadcastToWithSamplesOpProp method)
Inference (class in mxfusion.inference.inference)
inference_algorithm (mxfusion.inference.inference.Inference attribute)
InferenceAlgorithm (class in mxfusion.inference.inference_alg)
InferenceParameters (class in mxfusion.inference.inference_parameters)
init_outcomes() (in module mxfusion.util.inference)
initial_value (mxfusion.components.variables.variable.Variable attribute)
initialize() (mxfusion.inference.inference.Inference method)
initialize_params() (mxfusion.inference.inference_parameters.InferenceParameters method)
initialize_with_carryover_params() (mxfusion.inference.inference_parameters.InferenceParameters method)
input_names (mxfusion.components.factor.Factor attribute)
inputs (mxfusion.components.factor.Factor attribute)
inverseTransform() (mxfusion.components.variables.var_trans.Softplus method)
(mxfusion.components.variables.var_trans.VariableTransformation method)
is_sampled_array() (in module mxfusion.components.variables.runtime_variable)
K
K() (mxfusion.components.distributions.gp.kernels.kernel.Kernel method)
Kdiag() (mxfusion.components.distributions.gp.kernels.kernel.Kernel method)
Kernel (class in mxfusion.components.distributions.gp.kernels.kernel)
L
leaves (mxfusion.models.factor_graph.FactorGraph attribute)
Linear (class in mxfusion.components.distributions.gp.kernels.linear)
list_arguments() (mxfusion.util.customop.BroadcastToWithSamplesOpProp method)
list_outputs() (mxfusion.util.customop.BroadcastToWithSamplesOpProp method)
load() (mxfusion.inference.inference.Inference method)
load_configuration() (mxfusion.inference.inference.Inference method)
load_graph() (mxfusion.models.factor_graph.FactorGraph method)
load_parameters() (mxfusion.inference.inference_parameters.InferenceParameters static method)
local_parameters (mxfusion.components.distributions.gp.kernels.kernel.Kernel attribute)
log_cdf() (mxfusion.components.distributions.distribution.Distribution method)
log_pdf() (mxfusion.components.distributions.categorical.Categorical method)
(mxfusion.components.distributions.distribution.Distribution method)
(mxfusion.components.distributions.gp.cond_gp.ConditionalGaussianProcess method)
(mxfusion.components.distributions.gp.gp.GaussianProcess method)
(mxfusion.components.distributions.normal.MultivariateNormal method)
(mxfusion.components.distributions.normal.Normal method)
(mxfusion.components.distributions.pointmass.PointMass method)
LogPDFDecorator (class in mxfusion.components.distributions.distribution)
M
make_basic_model() (in module mxfusion.util.testutils)
make_bnn_model() (in module mxfusion.util.testutils)
make_net() (in module mxfusion.util.testutils)
MAP (class in mxfusion.inference.map)
merge_posterior_into_model() (in module mxfusion.inference.forward_sampling)
MinibatchInferenceLoop (class in mxfusion.inference.minibatch_loop)
MockMXNetRandomGenerator (class in mxfusion.util.testutils)
Model (class in mxfusion.models.model)
model (mxfusion.inference.inference_alg.InferenceAlgorithm attribute)
ModelComponent (class in mxfusion.components.model_component)
ModelComponentDecoder (class in mxfusion.util.graph_serialization)
ModelComponentEncoder (class in mxfusion.util.graph_serialization)
Module (class in mxfusion.components.modules.module)
modules (mxfusion.models.factor_graph.FactorGraph attribute)
MultivariateNormal (class in mxfusion.components.distributions.normal)
MultivariateNormalDrawSamplesDecorator (class in mxfusion.components.distributions.normal)
MultivariateNormalLogPDFDecorator (class in mxfusion.components.distributions.normal)
mxfusion (module)
mxfusion.components (module)
mxfusion.components.distributions (module)
mxfusion.components.distributions.categorical (module)
mxfusion.components.distributions.distribution (module)
mxfusion.components.distributions.gp (module)
mxfusion.components.distributions.gp.cond_gp (module)
mxfusion.components.distributions.gp.gp (module)
mxfusion.components.distributions.gp.kernels (module)
mxfusion.components.distributions.gp.kernels.add_kernel (module)
mxfusion.components.distributions.gp.kernels.kernel (module)
mxfusion.components.distributions.gp.kernels.linear (module)
mxfusion.components.distributions.gp.kernels.rbf (module)
mxfusion.components.distributions.gp.kernels.static (module)
mxfusion.components.distributions.gp.kernels.stationary (module)
mxfusion.components.distributions.normal (module)
mxfusion.components.distributions.pointmass (module)
mxfusion.components.distributions.random_gen (module)
mxfusion.components.distributions.univariate (module)
mxfusion.components.factor (module)
mxfusion.components.functions (module)
mxfusion.components.functions.function_evaluation (module)
mxfusion.components.functions.gluon_func_eval (module)
mxfusion.components.functions.mxfusion_gluon_function (module)
mxfusion.components.model_component (module)
mxfusion.components.modules (module)
mxfusion.components.modules.module (module)
mxfusion.components.variables (module)
mxfusion.components.variables.runtime_variable (module)
mxfusion.components.variables.var_trans (module)
mxfusion.components.variables.variable (module)
mxfusion.inference (module)
mxfusion.inference.batch_loop (module)
mxfusion.inference.forward_sampling (module)
mxfusion.inference.grad_based_inference (module)
mxfusion.inference.grad_loop (module)
mxfusion.inference.inference (module)
mxfusion.inference.inference_alg (module)
mxfusion.inference.inference_parameters (module)
mxfusion.inference.map (module)
mxfusion.inference.meanfield (module)
mxfusion.inference.minibatch_loop (module)
mxfusion.inference.variational (module)
mxfusion.models (module)
mxfusion.models.factor_graph (module)
mxfusion.models.model (module)
mxfusion.models.posterior (module)
mxfusion.util (module)
mxfusion.util.customop (module)
mxfusion.util.graph_serialization (module)
mxfusion.util.inference (module)
mxfusion.util.testutils (module)
mxfusion.util.util (module)
MXFusionGluonFunction (class in mxfusion.components.functions.mxfusion_gluon_function)
MXNetRandomGenerator (class in mxfusion.components.distributions.random_gen)
N
name (mxfusion.components.functions.mxfusion_gluon_function.MXFusionGluonFunction attribute)
NativeKernel (class in mxfusion.components.distributions.gp.kernels.kernel)
Normal (class in mxfusion.components.distributions.normal)
numpy_array_reshape() (in module mxfusion.util.testutils)
O
object_hook() (mxfusion.util.graph_serialization.ModelComponentDecoder method)
ObjectiveBlock (class in mxfusion.inference.inference_alg)
observed_variable_names (mxfusion.inference.inference.Inference attribute)
(mxfusion.inference.inference_alg.InferenceAlgorithm attribute)
observed_variable_UUIDs (mxfusion.inference.inference.Inference attribute)
(mxfusion.inference.inference_alg.InferenceAlgorithm attribute)
observed_variables (mxfusion.inference.inference.Inference attribute)
(mxfusion.inference.inference_alg.InferenceAlgorithm attribute)
ordered_factors (mxfusion.models.factor_graph.FactorGraph attribute)
output_names (mxfusion.components.factor.Factor attribute)
outputs (mxfusion.components.factor.Factor attribute)
P
param_dict (mxfusion.inference.inference_parameters.InferenceParameters attribute)
PARAMETER (mxfusion.components.variables.variable.VariableType attribute)
parameters (mxfusion.components.distributions.gp.kernels.kernel.CombinationKernel attribute)
(mxfusion.components.distributions.gp.kernels.kernel.Kernel attribute)
(mxfusion.components.distributions.gp.kernels.kernel.NativeKernel attribute)
parse_string_to_tuple() (in module mxfusion.util.util)
PointMass (class in mxfusion.components.distributions.pointmass)
PositiveTransformation (class in mxfusion.components.variables.var_trans)
Posterior (class in mxfusion.models.posterior)
posterior (mxfusion.inference.map.MAP attribute)
(mxfusion.inference.variational.StochasticVariationalInference attribute)
predecessors (mxfusion.components.model_component.ModelComponent attribute)
prepare_mxnet_array() (in module mxfusion.util.testutils)
R
RandomGenerator (class in mxfusion.components.distributions.random_gen)
RANDVAR (mxfusion.components.variables.variable.VariableType attribute)
RBF (class in mxfusion.components.distributions.gp.kernels.rbf)
realize_shape() (in module mxfusion.util.inference)
reconcile_graphs() (mxfusion.models.factor_graph.FactorGraph static method)
remove_component() (mxfusion.models.factor_graph.FactorGraph method)
remove_subgraph() (mxfusion.models.factor_graph.FactorGraph method)
rename_duplicate_names() (in module mxfusion.util.util)
replace_subgraph() (mxfusion.models.factor_graph.FactorGraph method)
replicate() (mxfusion.components.model_component.ModelComponent method)
replicate_self() (mxfusion.components.distributions.categorical.Categorical method)
(mxfusion.components.distributions.distribution.Distribution method)
(mxfusion.components.distributions.normal.MultivariateNormal method)
(mxfusion.components.factor.Factor method)
(mxfusion.components.functions.function_evaluation.FunctionEvaluation method)
(mxfusion.components.functions.gluon_func_eval.GluonFunctionEvaluation method)
(mxfusion.components.variables.variable.Variable method)
roots (mxfusion.models.factor_graph.FactorGraph attribute)
run() (mxfusion.inference.batch_loop.BatchInferenceLoop method)
(mxfusion.inference.grad_based_inference.GradBasedInference method)
(mxfusion.inference.grad_loop.GradLoop method)
(mxfusion.inference.inference.Inference method)
(mxfusion.inference.minibatch_loop.MinibatchInferenceLoop method)
S
sample_multinomial() (mxfusion.components.distributions.random_gen.MXNetRandomGenerator static method)
(mxfusion.util.testutils.MockMXNetRandomGenerator method)
sample_normal() (mxfusion.components.distributions.random_gen.MXNetRandomGenerator static method)
(mxfusion.components.distributions.random_gen.RandomGenerator static method)
(mxfusion.util.testutils.MockMXNetRandomGenerator method)
save() (mxfusion.inference.inference.Inference method)
(mxfusion.inference.inference_parameters.InferenceParameters method)
(mxfusion.models.factor_graph.FactorGraph method)
save_configuration() (mxfusion.inference.inference.Inference method)
set_intializer() (mxfusion.inference.inference.Inference method)
set_outputs() (mxfusion.components.factor.Factor method)
set_prior() (mxfusion.components.variables.variable.Variable method)
shape_str (mxfusion.components.variables.variable.Variable attribute)
slice_axis() (in module mxfusion.util.util)
Softplus (class in mxfusion.components.variables.var_trans)
StationaryKernel (class in mxfusion.components.distributions.gp.kernels.stationary)
StochasticVariationalInference (class in mxfusion.inference.variational)
successors (mxfusion.components.model_component.ModelComponent attribute)
T
TestBlock (class in mxfusion.util.testutils)
TransferInference (class in mxfusion.inference.inference)
transform() (mxfusion.components.variables.var_trans.Softplus method)
(mxfusion.components.variables.var_trans.VariableTransformation method)
transformation (mxfusion.components.variables.variable.Variable attribute)
type (mxfusion.components.variables.variable.Variable attribute)
U
UnivariateDistribution (class in mxfusion.components.distributions.univariate)
UnivariateDrawSamplesDecorator (class in mxfusion.components.distributions.univariate)
UnivariateLogPDFDecorator (class in mxfusion.components.distributions.univariate)
update_constants() (mxfusion.inference.inference_parameters.InferenceParameters method)
uuid (mxfusion.components.model_component.ModelComponent attribute)
V
var_ties (mxfusion.inference.inference_parameters.InferenceParameters attribute)
(mxfusion.models.factor_graph.FactorGraph attribute)
Variable (class in mxfusion.components.variables.variable)
variables (mxfusion.models.factor_graph.FactorGraph attribute)
variables_to_UUID() (in module mxfusion.util.inference)
VariableTransformation (class in mxfusion.components.variables.var_trans)
VariableType (class in mxfusion.components.variables.variable)
VariationalPosteriorForwardSampling (class in mxfusion.inference.forward_sampling)
W
White (class in mxfusion.components.distributions.gp.kernels.static)
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