Who Cited It

An Introduction to MCMC for Machine Learning

2003 · Machine Learning · 2,430 citations · 4 from inside this corpus

Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan

No abstract in the source record.

An Introduction to MCMC for Machine Learning (2003)An Introduction to MCMC for M…Novel approach to nonlinear/non-Gaussian Bayesian state estimation (1993)Novel approach to nonlinear/n…On sequential Monte Carlo sampling methods for Bayesian filtering (2000)On sequential Monte Carlo sam…Bayesian Learning for Neural Networks (1996)Bayesian Learning for Neural …Simulated Annealing: Theory and Applications (1987)Simulated Annealing: Theory a…Bayesian Density Estimation and Inference Using Mixtures (1995)Bayesian Density Estimation a…On Gibbs sampling for state space models (1994)On Gibbs sampling for state s…On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion) (1997)On Bayesian Analysis of Mixtu…Markov Chains and Stochastic Stability (2009)Markov Chains and Stochastic …Uncertainty in Artificial Intelligence (1992)Uncertainty in Artificial Int…The Unscented Particle Filter (2000)The Unscented Particle FilterLearning Deep Architectures for AI (2009)Learning Deep Architectures f…Incorporating non-local information into information extraction systems by Gibbs sampling (2005)Incorporating non-local infor…A Roadmap of Agent Research and Development (1998)A Roadmap of Agent Research a…Bayesian Cognitive Modeling: A Practical Course (2014)Bayesian Cognitive Modeling: …
14 of 14 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 this paper cites, inside the corpus

PaperYearCited
Novel approach to nonlinear/non-Gaussian Bayesian state estimation19937,639
On sequential Monte Carlo sampling methods for Bayesian filtering20004,459
Bayesian Learning for Neural Networks19964,397
Simulated Annealing: Theory and Applications19872,384
Bayesian Density Estimation and Inference Using Mixtures19952,248
On Gibbs sampling for state space models19941,986
On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion)19971,924
Markov Chains and Stochastic Stability20091,672
Uncertainty in Artificial Intelligence19921,436
The Unscented Particle Filter20001,419

What cites it, inside the corpus

PaperYearCited
Learning Deep Architectures for AI20095,077
Incorporating non-local information into information extraction systems by Gibbs sampling20053,044
A Roadmap of Agent Research and Development19982,099
Bayesian Cognitive Modeling: A Practical Course20141,423

Links

DOI · Open access copy · OpenAlex record

Topics

Bayesian Methods and Mixture ModelsComputer Science
Gaussian Processes and Bayesian InferenceComputer Science
Data Management and AlgorithmsComputer Science

Is this record sound?

complete

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

  • supports4 author record(s) attached.
  • supports196 reference(s) recorded.
  • 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…