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Keyword

structure learning

Description: A machine learning task that infers the structure of a model, such as dependencies in probabilistic graphical models or logic programs.
OpenAlex ID: keywords/structure-learning
A Bayesian Method for the Induction of Probabilistic Networks from Data
1992 · Gregory F. Cooper, Edward Herskovits · Machine Learning · 4,208
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Learning Bayesian Networks with the bnlearn R Package
2010 · Marco Scutari · Journal of Statistical Software · 1,737
Learning Bayesian Networks
2017 · Claude Sammut, Geoffrey I. Webb · Encyclopedia of Machine Learning and Data Mining · 1,424
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series
2021 · Ailin Deng, Bryan Hooi · Proceedings of the AAAI Conference on Artificial Intelligence · 1,400
The bayes net toolbox for matlab
2001 · Keelin Murphy · 1,016
Learning Structural Descriptions From Examples
1970 · Patrick Henry Winston · DSpace@MIT (Massachusetts Institute of Technology) · 995
Artificial Intelligence: Structures and Strategies for Complex Problem Solving
1989 · George F. Luger · 984
Learning Bayesian Belief Networks: an Approach Based on the Mdl Principle
1994 · Wai Lam, Fahiem Bacchus · Computational Intelligence · 758
The discovery of structural form
2008 · Charles Kemp, Joshua B. Tenenbaum · Proceedings of the National Academy of Sciences · 655
Modeling mutual context of object and human pose in human-object interaction activities
2010 · Bangpeng Yao, Li Fei-Fei · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 578
Learning the Structure of Dynamic Probabilistic Networks
2013 · Friedman, Nir, Murphy, Kevin, et al. · arXiv (Cornell University) · 561
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Learning Bayesian Networks
2005 · Marco F. Ramoni, Paola Sebastiani · IGI Global eBooks · 541
Learning the structure of event sequences.
1991 · Axel Cleeremans, James L. McClelland · Journal of Experimental Psychology General · 504
Bayesian networks
2009 · Finn V. Jensen · Wiley Interdisciplinary Reviews Computational Statistics · 476
A guide to the literature on learning probabilistic networks from data
1996 · W. Buntine · IEEE Transactions on Knowledge and Data Engineering · 468
Differentiable Learning of Logical Rules for Knowledge Base Reasoning
2017 · Yang, Fan, Yang, Zhilin, et al. · arXiv (Cornell University) · 410
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A survey of Bayesian Network structure learning
2023 · Neville Kenneth Kitson, Anthony C. Constantinou, et al. · Artificial Intelligence Review · 388
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Adaptive Probabilistic Networks with Hidden Variables
1997 · John Binder, Daphne Koller, et al. · Machine Learning · 377
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Bayesian Networks
2007 · Irad Ben‐Gal · Encyclopedia of Statistics in Quality and Reliability · 368
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Active Inference, Curiosity and Insight
2017 · Karl J. Friston, Marco Lin, et al. · Neural Computation · 352
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Learning Bayesian networks: approaches and issues
2011 · Rónán Daly, Qiang Shen, et al. · The Knowledge Engineering Review · 344
Learning latent structure: carving nature at its joints
2010 · Samuel J Gershman, Yael Niv · Current Opinion in Neurobiology · 323
A Bayesian Approach to Learning Bayesian Networks with Local Structure
2013 · Chickering, David Maxwell, Heckerman, David, et al. · arXiv (Cornell University) · 317
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A Primer on Learning in Bayesian Networks for Computational Biology
2007 · Chris J Needham, James R Bradford, et al. · PLoS Computational Biology · 311
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Learning Bayesian network classifiers by maximizing conditional likelihood
2004 · Daniel Grossman, Pedro Domingos · 308
Works count: 3,063
Citation count: 55,880
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