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  • 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: Hidden Markov Model
  • Example: Predator-Prey Model
  • Example: Neural Transport
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  • API Reference
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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
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