Who Cited It

Probabilistic machine learning and artificial intelligence

2015 · Nature · 2,031 citations · 7 from inside this corpus

Zoubin Ghahramani

No abstract in the source record.

Probabilistic machine learning and artificial intelligence (2015)Probabilistic machine learnin…A tutorial on hidden Markov models and selected applications in speech recognition (1989)A tutorial on hidden Markov m…Artificial intelligence: a modern approach (1995)Artificial intelligence: a mo…Bayesian Data Analysis (1995)Bayesian Data AnalysisArtificial intelligence: A modern approach (1996)Artificial intelligence: A mo…Gaussian Processes for Machine Learning (2005)Gaussian Processes for Machin…Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou… (2012)Deep Neural Networks for Acou…Machine learning a probabilistic perspective (2012)Machine learning a probabilis…Information theory, inference, and learning algorithms (2004)Information theory, inference…Probabilistic graphical models : principles and techniques (2009)Probabilistic graphical model…WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility (2000)WinBUGS - A Bayesian modellin…Information Theory, Inference, and Learning Algorithms (2004)Information Theory, Inference…A Bayesian Analysis of Some Nonparametric Problems (1973)A Bayesian Analysis of Some N…Bayesian Learning for Neural Networks (1996)Bayesian Learning for Neural …An Introduction to Variational Methods for Graphical Models (1999)An Introduction to Variationa…Neural Information Processing Systems (2018)Neural Information Processing…Hierarchical Dirichlet Processes (2006)Hierarchical Dirichlet Proces…Sequence to Sequence Learning with Neural Networks (2014)Sequence to Sequence Learning…Encyclopedia of Machine Learning (2010)Encyclopedia of Machine Learn…Pattern recognition and machine learning (2007)Pattern recognition and machi…How to Grow a Mind: Statistics, Structure, and Abstraction (2011)How to Grow a Mind: Statistic…Stochastic variational inference (2013)Stochastic variational infere…Expectation Propagation for approximate Bayesian inference (2013)Expectation Propagation for a…Uncertainty in Artificial Intelligence (1992)Uncertainty in Artificial Int…Deep learning and process understanding for data-driven Earth system science (2019)Deep learning and process und…Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning (2015)Dropout as a Bayesian Approxi…Human-level concept learning through probabilistic program induction (2015)Human-level concept learning …Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning (2015)Dropout as a Bayesian Approxi…How artificial intelligence will change the future of marketing (2019)How artificial intelligence w…Can we open the black box of AI? (2016)Automated Machine Learning (2019)Automated Machine Learning
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What this paper cites, inside the corpus

PaperYearCited
A tutorial on hidden Markov models and selected applications in speech recognition198922,910
Artificial intelligence: a modern approach199522,262
Bayesian Data Analysis199513,754
Artificial intelligence: A modern approach199610,703
Gaussian Processes for Machine Learning200510,470
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou…201210,399
Machine learning a probabilistic perspective20129,324
Information theory, inference, and learning algorithms20046,580
Probabilistic graphical models : principles and techniques20096,450
WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility20005,402
Information Theory, Inference, and Learning Algorithms20045,059
A Bayesian Analysis of Some Nonparametric Problems19734,833
Bayesian Learning for Neural Networks19964,397
An Introduction to Variational Methods for Graphical Models19993,793
Neural Information Processing Systems20183,765
Hierarchical Dirichlet Processes20063,580
Sequence to Sequence Learning with Neural Networks20143,514
Encyclopedia of Machine Learning20103,486
Pattern recognition and machine learning20072,691
How to Grow a Mind: Statistics, Structure, and Abstraction20111,923
Stochastic variational inference20131,480
Expectation Propagation for approximate Bayesian inference20131,460
Uncertainty in Artificial Intelligence19921,436

What cites it, inside the corpus

PaperYearCited
Deep learning and process understanding for data-driven Earth system science20195,475
Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning20154,187
Human-level concept learning through probabilistic program induction20152,958
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning20152,672
How artificial intelligence will change the future of marketing20192,670
Can we open the black box of AI?20161,751
Automated Machine Learning20191,451

Links

DOI · OpenAlex record

Topics

Gaussian Processes and Bayesian InferenceComputer Science
Advanced Bandit Algorithms ResearchDecision Sciences
Computability, Logic, AI AlgorithmsComputer Science

Is this record sound?

complete

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

  • supports1 author record(s) attached.
  • supports113 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 2026-09-04T03:58:51+00:00.

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