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0.9.1

Getting Started with NumPyro

API and Developer Reference

Pyro Primitives
Distributions
Inference
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
Truncated and folded distributions

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: Hidden Markov Model
Example: Hilbert space approximation for Gaussian processes.
Example: Predator-Prey Model
Example: Neural Transport
Example: Thompson sampling for Bayesian Optimization with GPs
Bayesian Hierarchical Stacking: Well Switching Case Study
Example: Sine-skewed sine (bivariate von Mises) mixture
Example: AR2 process
Example: Holt-Winters Exponential Smoothing
Example: Zero-Inflated Poisson regression model

Other Inference Algorithms

Example: MCMC Methods for Tall Data
Example: Hamiltonian Monte Carlo with Energy Conserving Subsampling
Example: Bayesian Neural Network with SteinVI
Example: Deep Markov Model inferred using SteinVI

NumPyro

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