NumPyro
0.6.0
Getting Started with NumPyro
API and Developer Reference
API Reference
Modeling
Pyro Primitives
Effect Handlers
Distributions
Base Distribution
Continuous Distributions
Discrete Distributions
Directional Distributions
TensorFlow Distributions
Constraints
Transforms
Flows
Inference
Markov Chain Monte Carlo (MCMC)
Stochastic Variational Inference (SVI)
Automatic Guide Generation
Reparameterizers
Funsor-based NumPyro
Optimizers
Diagnostics
Runtime Utilities
Inference Utilities
Change Log
Introductory Tutorials
Bayesian Regression Using NumPyro
Bayesian Hierarchical Linear Regression
Example: Baseball Batting Average
Example: Variational Autoencoder
Example: Neal’s Funnel
Example: Stochastic Volatility
Discrete Latent Variables
Example: Bayesian Models of Annotation
Example: Enumerate Hidden Markov Model
Example: CJS Capture-Recapture Model for Ecological Data
Bayesian Imputation for Missing Values in Discrete Covariates
Applications
Time Series Forecasting
Ordinal Regression
Bayesian Imputation
Example: Gaussian Process
Example: Bayesian Neural Network
Example: Sparse Regression
Example: Proportion Test
Example: Generalized Linear Mixed Models
Example: Hamiltonian Monte Carlo with Energy Conserving Subsampling
Example: Hidden Markov Model
Example: Predator-Prey Model
Example: Neural Transport
Example: MCMC Methods for Tall Data
NumPyro
Docs
»
API Reference
Edit on GitHub
API Reference
¶
Modeling
¶
Pyro Primitives
Effect Handlers
Distributions
¶
Base Distribution
Continuous Distributions
Discrete Distributions
Directional Distributions
TensorFlow Distributions
Constraints
Transforms
Flows
Inference
¶
Markov Chain Monte Carlo (MCMC)
Stochastic Variational Inference (SVI)
Automatic Guide Generation
Reparameterizers
Funsor-based NumPyro
Optimizers
Diagnostics
Runtime Utilities
Inference Utilities