Who Cited It

Pattern Recognition and Neural Networks

1996 · Cambridge University Press eBooks · 6,514 citations · 16 from inside this corpus

B. D. Ripley

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.

Pattern Recognition and Neural Networks (1996)Pattern Recognition and Neura…The Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…Support-Vector Networks (1995)Support-Vector NetworksNeural networks for pattern recognition (1994)Neural networks for pattern r…Bagging Predictors (1996)Bagging PredictorsIntroduction to Statistical Pattern Recognition (1990)Introduction to Statistical P…Self-Organizing Maps (1995)Self-Organizing MapsThe self-organizing map (1990)The self-organizing mapExperiments with a new boosting algorithm (1996)Experiments with a new boosti…Random decision forests (2002)Random decision forestsInstance-Based Learning Algorithms (1991)Instance-Based Learning Algor…The Handbook of brain theory and neural networks (1996)The Handbook of brain theory …The Strength of Weak Learnability (1990)The Strength of Weak Learnabi…Neural Network Ensembles, Cross Validation, and Active Learning (1994)Boosting a Weak Learning Algorithm by Majority (1995)Boosting a Weak Learning Algo…Greedy function approximation: A gradient boosting machine. (2001)Greedy function approximation…The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2010)The Elements of Statistical L…Gaussian Processes for Machine Learning (2005)Gaussian Processes for Machin…Bayesian Network Classifiers (1997)Model-Based Clustering, Discriminant Analysis, and Density Estimation (2002)Model-Based Clustering, Discr…Semi-Supervised Learning (2006)Semi-Supervised LearningSupport Vector Data Description (2003)Support Vector Data Descripti…Introduction to Bayesian Networks (2019)Introduction to Bayesian Netw…A gentle tutorial of the em algorithm and its application to parameter estimation for Gau… (1998)A gentle tutorial of the em a…Logistic regression and artificial neural network classification models: a methodology re… (2002)Logistic regression and artif…On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation (2010)On Over-fitting in Model Sele…Fundamentals of Artificial Neural Networks (1996)Fundamentals of Artificial Ne…Ensemble Machine Learning (2012)Ensemble Machine LearningApproximation theory of the MLP model in neural networks (1999)Approximation theory of the M…Pattern Recognition and Machine Learning (2007)Pattern Recognition and Machi…Feature subset selection using a genetic algorithm (1998)Feature subset selection usin…
30 of 30 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.
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What this paper cites, inside the corpus

PaperYearCited
The Nature of Statistical Learning Theory199539,409
Support-Vector Networks199533,914
Neural networks for pattern recognition199418,720
Bagging Predictors199617,191
Introduction to Statistical Pattern Recognition199011,140
Self-Organizing Maps199510,390
The self-organizing map19908,234
Experiments with a new boosting algorithm19967,582
Random decision forests20025,123
Instance-Based Learning Algorithms19914,128
The Handbook of brain theory and neural networks19963,915
The Strength of Weak Learnability19903,344
Neural Network Ensembles, Cross Validation, and Active Learning19941,803
Boosting a Weak Learning Algorithm by Majority19951,691

What cites it, inside the corpus

PaperYearCited
Greedy function approximation: A gradient boosting machine.200130,137
The Elements of Statistical Learning: Data Mining, Inference, and Prediction201012,807
Gaussian Processes for Machine Learning200510,470
Bayesian Network Classifiers19974,754
Model-Based Clustering, Discriminant Analysis, and Density Estimation20024,342
Semi-Supervised Learning20064,334
Support Vector Data Description20033,526
Introduction to Bayesian Networks20192,594
A gentle tutorial of the em algorithm and its application to parameter estimation for Gau…19982,510
Logistic regression and artificial neural network classification models: a methodology re…20022,201
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation20101,988
Fundamentals of Artificial Neural Networks19961,902
Ensemble Machine Learning20121,653
Approximation theory of the MLP model in neural networks19991,548
Pattern Recognition and Machine Learning20071,390
Feature subset selection using a genetic algorithm19981,369

Links

DOI · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Face and Expression RecognitionComputer Science
Spectroscopy and Chemometric AnalysesChemistry

Is this record sound?

complete

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

  • supports1 author record(s) attached.
  • supports102 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 2026-09-04T03:58:43+00:00.

sha256 5cad55ac5d4d41e1…