Who Cited It

Learning in Graphical Models

1998 · 2,437 citations · 19 from inside this corpus

Michael I. Jordan

No abstract in the source record.

Learning in Graphical Models (1998)Learning in Graphical ModelsLatent dirichlet allocation (2003)Latent dirichlet allocationGaussian Processes in Machine Learning (2004)Gaussian Processes in Machine…Learning Deep Architectures for AI (2009)Learning Deep Architectures f…Training Products of Experts by Minimizing Contrastive Divergence (2002)Training Products of Experts …Semi-Supervised Learning (2006)Semi-Supervised LearningBayesian Networks and Decision Graphs (2007)Bayesian Networks and Decisio…Supervised Machine Learning: A Review of Classification Techniques (2007)Supervised Machine Learning: …An Introduction to Variational Methods for Graphical Models (1999)An Introduction to Variationa…Text Classification from Labeled and Unlabeled Documents using EM (2000)Text Classification from Labe…Kalman Filtering and Neural Networks (2001)Kalman Filtering and Neural N…Ant colony optimization theory: A survey (2005)Ant colony optimization theor…Graph Signal Processing: Overview, Challenges, and Applications (2018)Graph Signal Processing: Over…A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions (2018)A tutorial on Gaussian proces…Variational Algorithms for Approximate Bayesian Inference (2003)Variational Algorithms for Ap…Machine learning: a review of classification and combining techniques (2006)Machine learning: a review of…GAUSSIAN PROCESSES FOR MACHINE LEARNING (2004)GAUSSIAN PROCESSES FOR MACHIN…Stochastic variational inference (2013)Stochastic variational infere…Adaptive Computation and Machine Learning (2012)Adaptive Computation and Mach…Explaining nonlinear classification decisions with deep Taylor decomposition (2016)
19 of 19 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What cites it, inside the corpus

PaperYearCited
Latent dirichlet allocation200327,078
Gaussian Processes in Machine Learning20045,173
Learning Deep Architectures for AI20095,077
Training Products of Experts by Minimizing Contrastive Divergence20025,032
Semi-Supervised Learning20064,334
Bayesian Networks and Decision Graphs20074,152
Supervised Machine Learning: A Review of Classification Techniques20074,149
An Introduction to Variational Methods for Graphical Models19993,793
Text Classification from Labeled and Unlabeled Documents using EM20002,753
Kalman Filtering and Neural Networks20012,404
Ant colony optimization theory: A survey20052,308
Graph Signal Processing: Overview, Challenges, and Applications20181,817
A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions20181,743
Variational Algorithms for Approximate Bayesian Inference20031,736
Machine learning: a review of classification and combining techniques20061,562
GAUSSIAN PROCESSES FOR MACHINE LEARNING20041,486
Stochastic variational inference20131,480
Adaptive Computation and Machine Learning20121,437
Explaining nonlinear classification decisions with deep Taylor decomposition20161,413

Links

DOI · OpenAlex record

Topics

Machine Learning and AlgorithmsComputer Science

Is this record sound?

partial

One field of this record is missing or disagrees with another. What is shown below is what the source publishes.

  • supports1 author record(s) attached.
  • weakensNo references are recorded despite 2,437 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:49+00:00.

sha256 a2172c1bbe00c44b…