NumPyro
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Getting Started with NumPyro
API and Developer Reference
Pyro Primitives
Distributions
Inference
Markov Chain Monte Carlo (MCMC)
Stochastic Variational Inference (SVI)
Automatic Guide Generation
Reparameterizers
Funsor-based NumPyro
Optimizers
Diagnostics
Runtime Utilities
Inference Utilities
Visualization Utilities
Effect Handlers
Contributed Code
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
Example: ProdLDA with Flax and Haiku
Automatic rendering of NumPyro models
Bad posterior geometry and how to deal with it
Discrete Latent Variables
Example: Bayesian Models of Annotation
Example: Enumerate Hidden Markov Model
Example: CJS Capture-Recapture Model for Ecological Data
Example: Nested Sampling for Gaussian Shells
Bayesian Imputation for Missing Values in Discrete Covariates
Applications
Time Series Forecasting
Ordinal Regression
Bayesian Imputation
Example: Gaussian Process
Example: Bayesian Neural Network
Example: AutoDAIS
Example: Sparse Regression
Example: Horseshoe Regression
Example: Proportion Test
Example: Generalized Linear Mixed Models
Example: Hamiltonian Monte Carlo with Energy Conserving Subsampling
Example: Hidden Markov Model
Example: Hilbert space approximation for Gaussian processes.
Example: Predator-Prey Model
Example: Neural Transport
Example: MCMC Methods for Tall Data
Example: Thompson sampling for Bayesian Optimization with GPs
NumPyro
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Inference
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Inference
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Markov Chain Monte Carlo (MCMC)
Stochastic Variational Inference (SVI)
Automatic Guide Generation
Reparameterizers
Funsor-based NumPyro
Optimizers
Diagnostics
Runtime Utilities
Inference Utilities
Visualization Utilities
Read the Docs
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