Graphical Models, Exponential Families, and Variational Inference
Martin J. Wainwright, Michael I. Jordan
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- Probabilistic topic models→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Semi-Supervised Learning→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Graph Signal Processing: Overview, Challenges, and Applications→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Kernel methods in machine learning→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Hidden factors and hidden topics→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Mixed Membership Stochastic Blockmodels.→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Variational inference for Dirichlet process mixtures→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Stochastic variational inference→Graphical Models, Exponential Families, and Variational InferenceLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Latent dirichlet allocationLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Introduction to AlgorithmsLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Probabilistic Reasoning in Intelligent Systems: Networks of Plausible InferenceLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Foundations of statistical natural language processingLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Fundamentals of speech recognitionLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Local Computations with Probabilities on Graphical Structures and Their Application to Ex…Legacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→An Introduction to Variational Methods for Graphical ModelsLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→A View of the Em Algorithm that Justifies Incremental, Sparse, and other VariantsLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Methods of Information GeometryLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Variational Algorithms for Approximate Bayesian InferenceLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→On the inherent intractability of certain coding problems (Corresp.)Legacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Variational inference for Dirichlet process mixturesLegacy edge — source detail unavailable
- Graphical Models, Exponential Families, and Variational Inference→Expectation Propagation for approximate Bayesian inferenceLegacy edge — source detail unavailable
- Semi-Supervised Learning→A View of the Em Algorithm that Justifies Incremental, Sparse, and other VariantsLegacy edge — source detail unavailable
- An Introduction to Variational Methods for Graphical Models→Probabilistic Reasoning in Intelligent Systems: Networks of Plausible InferenceLegacy edge — source detail unavailable
- An Introduction to Variational Methods for Graphical Models→A View of the Em Algorithm that Justifies Incremental, Sparse, and other VariantsLegacy edge — source detail unavailable
- Latent dirichlet allocation→An Introduction to Variational Methods for Graphical ModelsLegacy edge — source detail unavailable
- Hidden factors and hidden topics→Latent dirichlet allocationLegacy edge — source detail unavailable
- Mixed Membership Stochastic Blockmodels.→An Introduction to Variational Methods for Graphical ModelsLegacy edge — source detail unavailable
- Mixed Membership Stochastic Blockmodels.→Latent dirichlet allocationLegacy edge — source detail unavailable
- Variational Algorithms for Approximate Bayesian Inference→An Introduction to Variational Methods for Graphical ModelsLegacy edge — source detail unavailable
- Variational Algorithms for Approximate Bayesian Inference→Local Computations with Probabilities on Graphical Structures and Their Application to Ex…Legacy edge — source detail unavailable
- Variational Algorithms for Approximate Bayesian Inference→Probabilistic Reasoning in Intelligent Systems: Networks of Plausible InferenceLegacy edge — source detail unavailable
- Variational Algorithms for Approximate Bayesian Inference→A View of the Em Algorithm that Justifies Incremental, Sparse, and other VariantsLegacy edge — source detail unavailable
- Variational inference for Dirichlet process mixtures→An Introduction to Variational Methods for Graphical ModelsLegacy edge — source detail unavailable
- Variational inference for Dirichlet process mixtures→Latent dirichlet allocationLegacy edge — source detail unavailable
- Variational inference for Dirichlet process mixtures→Variational Algorithms for Approximate Bayesian InferenceLegacy edge — source detail unavailable
- Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference→Local Computations with Probabilities on Graphical Structures and Their Application to Ex…Legacy edge — source detail unavailable
- Stochastic variational inference→An Introduction to Variational Methods for Graphical ModelsLegacy edge — source detail unavailable
- Stochastic variational inference→Latent dirichlet allocationLegacy edge — source detail unavailable
- Stochastic variational inference→Variational inference for Dirichlet process mixturesLegacy edge — source detail unavailable
- Stochastic variational inference→Probabilistic Reasoning in Intelligent Systems: Networks of Plausible InferenceLegacy edge — source detail unavailable
- Stochastic variational inference→Probabilistic topic modelsLegacy edge — source detail unavailable
- Probabilistic topic models→An Introduction to Variational Methods for Graphical ModelsLegacy edge — source detail unavailable
- Probabilistic topic models→Latent dirichlet allocationLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→An Introduction to Variational Methods for Graphical ModelsLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Local Computations with Probabilities on Graphical Structures and Their Application to Ex…Legacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Latent dirichlet allocationLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Expectation Propagation for approximate Bayesian inferenceLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Mixed Membership Stochastic Blockmodels.Legacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Variational inference for Dirichlet process mixturesLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Probabilistic Reasoning in Intelligent Systems: Networks of Plausible InferenceLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Stochastic variational inferenceLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Probabilistic topic modelsLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→A View of the Em Algorithm that Justifies Incremental, Sparse, and other VariantsLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Probabilistic topic models | 2012 | 5,623 |
| Semi-Supervised Learning | 2006 | 4,334 |
| Variational Inference: A Review for Statisticians | 2023 | 2,169 |
| Graph Signal Processing: Overview, Challenges, and Applications | 2018 | 1,817 |
| Kernel methods in machine learning | 2008 | 1,618 |
| Hidden factors and hidden topics | 2013 | 1,610 |
| Mixed Membership Stochastic Blockmodels. | 2008 | 1,540 |
| Variational inference for Dirichlet process mixtures | 2006 | 1,489 |
| Stochastic variational inference | 2013 | 1,480 |
Links
Topics
| Algorithms and Data Compression | Computer Science |
| Bayesian Methods and Mixture Models | Computer Science |
| Bayesian Modeling and Causal Inference | Computer Science |
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