Variational Inference: A Review for Statisticians
Explore this paper's citation graph
Summary
Variational inference (VI), a method from machine learning that approximates probability densities through optimization, is reviewed and a variant that uses stochastic optimization to scale up to massive data is derived.
- Type
- article
- Published
- 2016-01-04
- Cited by
- 5,907
- References
- 187
- Access
- Open access
- OpenAlex
- https://openalex.org/W2225156818
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3554631
Keywords
Exponential family, Closeness, Markov chain Monte Carlo, Inference, Bayesian inference
References
- Laplace Variational Approximation for Semiparametric Regression in the Presence of Heteroskedastic Errors
- Bayesian Gaussian Process Latent Variable Model
- Ensemble learning in Bayesian neural networks
- Monte Carlo Statistical Methods (Springer Texts in Statistics)
- Introduction to stochastic search and optimization - estimation, simulation, and control
- Bounded Approximations for Marginal Likelihoods
- Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models
- Scalable Variational Inference for Bayesian Variable Selection in Regression, and Its Accuracy in Genetic Association Studies
- A Bayesian approach for place recognition
- Bayesian parameter estimation via variational methods
- Pattern Recognition and Machine Learning
- An Introduction to Variational Methods for Graphical Models
- Mean Field Theory for Sigmoid Belief Networks
- Factorial Hidden Markov Models
- Divergence measures and message passing
- A variational Bayes spatiotemporal model for electromagnetic brain mapping
- On Information and Sufficiency
- Variational Cumulant Expansions for Intractable Distributions
- Mean field variational bayes for elaborate distributions
- Bayesian reasoning and machine learning
Cited by
- Fast Maximum Likelihood Estimation via Equilibrium Expectation for Large Network Data
- A UNIFIED STATISTICAL FRAMEWORK FOR SINGLE CELL AND BULK RNA SEQUENCING DATA
- Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees
- Exact and approximate inference in graphical models: variable elimination and beyond
- Scaling the Gibbs posterior credible regions
- A Variational Approximations-DIC Rubric for Parameter Estimation and Mixture Model Selection Within a Family Setting
- Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation
- Neuron’s eye view: Inferring features of complex stimuli from neural responses
- Relative entropy minimization over Hilbert spaces via Robbins-Monro
- Accelerating Monte Carlo methods for Bayesian inference in dynamical models
- Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains
- Posterior Dispersion Indices
- Extreme Stochastic Variational Inference: Distributed and Asynchronous
- Probabilistic Data Analysis with Probabilistic Programming
- Efficient real-time monitoring of an emerging influenza epidemic: how feasible?
- Sparse estimation of multivariate Poisson log‐normal models from count data
- Modeling Grasp Motor Imagery
- Rejection Sampling Variational Inference
- Bayesian Nonnegative CP Decomposition-Based Feature Extraction Algorithm for Drowsiness Detection
- Optimal Belief Approximation