Who Cited It

Stochastic variational inference

2013 · Journal of Machine Learning Research · 1,480 citations · 5 from inside this corpus

Matthew D. Hoffman low, David M. Blei, Chong Wang, John Paisley low

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Stochastic variational inference (2013)Stochastic variational infere…A New Approach to Linear Filtering and Prediction Problems (1960)A New Approach to Linear Filt…Latent dirichlet allocation (2003)Latent dirichlet allocationA tutorial on hidden Markov models and selected applications in speech recognition (1989)A tutorial on hidden Markov m…Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (1988)Probabilistic Reasoning in In…Machine learning a probabilistic perspective (2012)Machine learning a probabilis…Pattern Recognition and Machine Learning (Information Science and Statistics) (2006)Pattern Recognition and Machi…Probabilistic graphical models : principles and techniques (2009)Probabilistic graphical model…Finding scientific topics (2004)Finding scientific topicsProbabilistic topic models (2012)Probabilistic topic modelsA Bayesian Analysis of Some Nonparametric Problems (1973)A Bayesian Analysis of Some N…An Introduction to Variational Methods for Graphical Models (1999)An Introduction to Variationa…Hierarchical Dirichlet Processes (2006)Hierarchical Dirichlet Proces…Graphical Models, Exponential Families, and Variational Inference (2007)Graphical Models, Exponential…Learning in Graphical Models (1998)Learning in Graphical ModelsDynamic topic models (2006)Dynamic topic modelsBayesian Density Estimation and Inference Using Mixtures (1995)Bayesian Density Estimation a…Markov Chain Sampling Methods for Dirichlet Process Mixture Models (2000)Markov Chain Sampling Methods…Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems (1974)Mixtures of Dirichlet Process…Introduction to Stochastic Search and Optimization (2003)Introduction to Stochastic Se…Variational inference for Dirichlet process mixtures (2006)Variational inference for Dir…Bayesian learning via stochastic gradient langevin dynamics (2011)Bayesian learning via stochas…Auto-Encoding Variational Bayes (2013)Auto-Encoding Variational Bay…Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning (2015)Dropout as a Bayesian Approxi…Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning (2015)Dropout as a Bayesian Approxi…Variational Inference: A Review for Statisticians (2023)Variational Inference: A Revi…Probabilistic machine learning and artificial intelligence (2015)Probabilistic machine learnin…
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What this paper cites, inside the corpus

PaperYearCited
A New Approach to Linear Filtering and Prediction Problems196031,488
Latent dirichlet allocation200327,078
A tutorial on hidden Markov models and selected applications in speech recognition198922,910
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference198816,981
Machine learning a probabilistic perspective20129,324
Pattern Recognition and Machine Learning (Information Science and Statistics)20068,359
Probabilistic graphical models : principles and techniques20096,450
Finding scientific topics20046,082
Probabilistic topic models20125,623
A Bayesian Analysis of Some Nonparametric Problems19734,833
An Introduction to Variational Methods for Graphical Models19993,793
Hierarchical Dirichlet Processes20063,580
Graphical Models, Exponential Families, and Variational Inference20073,171
Learning in Graphical Models19982,437
Dynamic topic models20062,414
Bayesian Density Estimation and Inference Using Mixtures19952,248
Markov Chain Sampling Methods for Dirichlet Process Mixture Models20002,217
Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems19742,035
Introduction to Stochastic Search and Optimization20031,911
Variational inference for Dirichlet process mixtures20061,489
Bayesian learning via stochastic gradient langevin dynamics20111,487

What cites it, inside the corpus

PaperYearCited
Auto-Encoding Variational Bayes201315,583
Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning20154,187
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning20152,672
Variational Inference: A Review for Statisticians20232,169
Probabilistic machine learning and artificial intelligence20152,031

Links

DOI · OpenAlex record

Topics

Bayesian Methods and Mixture ModelsComputer Science
Gaussian Processes and Bayesian InferenceComputer Science
Statistical Methods and InferenceMathematics

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports4 author record(s) attached.
  • supports97 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

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