Pyro Core:
Getting Started
Primitives
Inference
Distributions
Parameters
Neural Networks
Optimization
Poutine (Effect handlers)
Miscellaneous Ops
Settings
Testing Utilities
Contributed Code:
Automatic Name Generation
Bayesian Neural Networks
Causal Effect VAE
Easy Custom Guides
Epidemiology
Pyro Examples
Forecasting
Funsor-based Pyro
Gaussian Processes
Minipyro
Biological Sequence Models with MuE
Optimal Experiment Design
Random Variables
Time Series
Tracking
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Pyro Documentation
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Pyro Core:
Getting Started
Primitives
Inference
SVI
ELBO
Importance
Reweighted Wake-Sleep
Sequential Monte Carlo
Stein Methods
Likelihood free methods
Discrete Inference
Prediction utilities
MCMC
Automatic Guide Generation
Reparameterizers
Inference utilities
Distributions
PyTorch Distributions
Pyro Distributions
Transforms
TransformModules
Transform Factories
Constraints
Parameters
ParamStore
Neural Networks
Pyro Modules
AutoRegressiveNN
DenseNN
ConditionalAutoRegressiveNN
ConditionalDenseNN
Optimization
Pyro Optimizers
PyTorch Optimizers
Higher-Order Optimizers
Poutine (Effect handlers)
Handlers
Trace
Runtime
Utilities
Messengers
Miscellaneous Ops
Utilities for HMC
Newton Optimizers
Special Functions
Tensor Utilities
Tensor Indexing
Tensor Contraction
Gaussian Contraction
Statistical Utilities
Streaming Statistics
State Space Model and GP Utilities
Settings
Default Settings
Settings Interface
Testing Utilities
Goodness of Fit Testing
Contributed Code:
Automatic Name Generation
Named Data Structures
Scoping
Bayesian Neural Networks
HiddenLayer
Causal Effect VAE
CEVAE Class
CEVAE Components
Utilities
Easy Custom Guides
EasyGuide
easy_guide
Group
Epidemiology
Base Compartmental Model
Example Models
Distributions
Pyro Examples
Datasets
Utilities
Forecasting
Forecaster Interface
Evaluation
Funsor-based Pyro
Primitives
Effect handlers
Inference algorithms
Gaussian Processes
Models
Kernels
Likelihoods
Parameterized
Util
Minipyro
Mini Pyro
Biological Sequence Models with MuE
Example MuE Models
State Arrangers for Parameterizing MuEs
Missing or Variable Length Data HMM
Biosequence Dataset Loading
Optimal Experiment Design
Expected Information Gain
Generalised Linear Mixed Models
Random Variables
Random Variable
Time Series
Abstract Models
Gaussian Processes
Linear Gaussian State Space Models
Tracking
Data Association
Distributions
Dynamic Models
Extended Kalman Filter
Hashing
Measurements
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Indices and tables
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