Works matching DE "GRAPHICAL modeling (Statistics)"
Results: 906
Azeotropic Distillation: A Review of Mathematical Models.
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- Separation & Purification Reviews, 2005, v. 34, n. 1, p. 87, doi. 10.1081/SPM-200054984
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Editorial: Errors of the Third Kind.
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- Journal of Parapsychology, 2019, v. 83, n. 2, p. 117, doi. 10.30891/jopar.2019.02.01
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Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes.
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- Machine Learning, 2018, v. 107, n. 8-10, p. 1303, doi. 10.1007/s10994-018-5718-0
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Learning undirected graphical models using persistent sequential Monte Carlo.
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- Machine Learning, 2016, v. 103, n. 2, p. 239, doi. 10.1007/s10994-016-5564-x
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Probabilistic combination of classification rules and its application to medical diagnosis.
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- Machine Learning, 2015, v. 101, n. 1-3, p. 105, doi. 10.1007/s10994-015-5508-x
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Lifted graphical models: a survey.
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- Machine Learning, 2015, v. 99, n. 1, p. 1, doi. 10.1007/s10994-014-5443-2
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Exploiting symmetries for scaling loopy belief propagation and relational training.
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- Machine Learning, 2013, v. 92, n. 1, p. 91, doi. 10.1007/s10994-013-5385-0
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Learning graphical models for relational data via lattice search.
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- Machine Learning, 2012, v. 88, n. 3, p. 331, doi. 10.1007/s10994-012-5289-4
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Statistical topic models for multi-label document classification.
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- Machine Learning, 2012, v. 88, n. 1-2, p. 157, doi. 10.1007/s10994-011-5272-5
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Optimal control as a graphical model inference problem.
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- Machine Learning, 2012, v. 87, n. 2, p. 159, doi. 10.1007/s10994-012-5278-7
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Gradient-based boosting for statistical relational learning: The relational dependency network case.
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- Machine Learning, 2012, v. 86, n. 1, p. 25, doi. 10.1007/s10994-011-5244-9
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Creating non-minimal triangulations for use in inference in mixed stochastic/deterministic graphical models.
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- Machine Learning, 2011, v. 84, n. 3, p. 249, doi. 10.1007/s10994-010-5233-4
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Estimating variable structure and dependence in multitask learning via gradients.
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- Machine Learning, 2011, v. 83, n. 3, p. 265, doi. 10.1007/s10994-010-5217-4
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Learning multi-linear representations of distributions for efficient inference.
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- Machine Learning, 2009, v. 76, n. 2-3, p. 195, doi. 10.1007/s10994-009-5130-x
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Bayesian learning of graphical vector autoregressions with unequal lag-lengths.
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- Machine Learning, 2009, v. 75, n. 2, p. 217, doi. 10.1007/s10994-009-5101-2
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Latent grouping models for user preference prediction.
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- Machine Learning, 2009, v. 74, n. 1, p. 75, doi. 10.1007/s10994-008-5081-7
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Boosted Bayesian network classifiers.
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- Machine Learning, 2008, v. 73, n. 2, p. 155, doi. 10.1007/s10994-008-5065-7
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New closed-form bounds on the partition function.
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- Machine Learning, 2008, v. 72, n. 3, p. 205
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Learning the structure of dynamic Bayesian networks from time series and steady state measurements.
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- Machine Learning, 2008, v. 71, n. 2-3, p. 185
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Aligning music audio with symbolic scores using a hybrid graphical model.
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- Machine Learning, 2006, v. 65, n. 2-3, p. 389, doi. 10.1007/s10994-006-8415-3
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Modeling, analyzing, and synthesizing expressive piano performance with graphical models.
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- Machine Learning, 2006, v. 65, n. 2-3, p. 361, doi. 10.1007/s10994-006-8751-3
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Markov logic networks.
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- Machine Learning, 2006, v. 62, n. 1-2, p. 107, doi. 10.1007/s10994-006-5833-1
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Integrating Uncertain Preferences into Status Quo Analysis with Applications to an Environmental Conflict.
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- Group Decision & Negotiation, 2005, v. 14, n. 6, p. 461, doi. 10.1007/s10726-005-9003-9
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The Graph Model for Conflict Resolution: Past, Present, and Future.
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- Group Decision & Negotiation, 2005, v. 14, n. 6, p. 441, doi. 10.1007/s10726-005-9002-x
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Multigraphs with Δ ≥ 3 are Totally-(2Δ−1)-Choosable.
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- Graphs & Combinatorics, 2009, v. 25, n. 1, p. 35, doi. 10.1007/s00373-008-0817-5
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Trade Spectrum of K <sub>4</sub> − e.
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- Graphs & Combinatorics, 2005, v. 21, n. 4, p. 475, doi. 10.1007/s00373-005-0633-0
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Graphical methods for investigating the size and power of hypothesis tests.
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- Manchester School (1463-6786), 1998, v. 66, n. 1, p. 1, doi. 10.1111/1467-9957.00086
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Simplified Method for Quantifying Theoretical Underestimation of Chamber-Based Trace Gas Fluxes.
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- Journal of Environmental Quality, 2010, v. 39, n. 1, p. 126, doi. 10.2134/jeq2009.0231
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- Article
Modeling the Variability of Sydney Harbor Wind Measurements.
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- Journal of Applied Meteorology (1988), 2003, v. 42, n. 8, p. 1131, doi. 10.1175/1520-0450(2003)042<1131:MTVOSH>2.0.CO;2
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High-dimensional rank-based graphical models for non-Gaussian functional data.
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- Statistics, 2023, v. 57, n. 2, p. 388, doi. 10.1080/02331888.2023.2201009
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Missing sensor network data.
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- Communications in Statistics: Case Studies & Data Analysis, 2019, v. 5, n. 2, p. 163, doi. 10.1080/23737484.2018.1563513
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Graphical and statistical comparison of various size distribution measurement systems using metal powders of a range of sizes and shapes.
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- Powder Metallurgy, 2011, v. 54, n. 4, p. 497, doi. 10.1179/003258910X12707304455022
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Three new diagnostic verification diagrams.
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- Meteorological Applications, 2016, v. 23, n. 3, p. 371, doi. 10.1002/met.1561
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An Ecology of Brands, Art and Control The New Age of Homo Cypiens.
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- Arte y Políticas de Identidad, 2014, v. 10, n. 11, p. 279
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Web applications design recovery and evolution with RE-UWA.
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- Journal of Software: Evolution & Process, 2013, v. 25, n. 8, p. 789, doi. 10.1002/smr.1561
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Weighted Fused Pathway Graphical Lasso for Joint Estimation of Multiple Gene Networks.
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- Frontiers in Genetics, 2019, p. 1, doi. 10.3389/fgene.2019.00623
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- Article
Microbial Networks in SPRING - Semi-parametric Rank-Based Correlation and Partial Correlation Estimation for Quantitative Microbiome Data.
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- Frontiers in Genetics, 2019, p. N.PAG, doi. 10.3389/fgene.2019.00516
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Graphical Analysis of Test Items.
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- Educational Research & Evaluation, 2002, v. 8, n. 3, p. 319, doi. 10.1076/edre.8.3.319.3856
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NOTES AND COMMENTS. SOME OBSERVATIONS ON FRACTILE GRAPHICAL ANALYSIS.
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- Econometrica, 1965, v. 33, n. 3, p. 644, doi. 10.2307/1911761
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Confirmatory path analysis in a generalized multilevel context.
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- Ecology, 2009, v. 90, n. 2, p. 363, doi. 10.1890/08-1034.1
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- Article
Learning the Structure of Mixed Graphical Models.
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- Journal of Computational & Graphical Statistics, 2015, v. 24, n. 1, p. 230, doi. 10.1080/10618600.2014.900500
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A Localized Implementation of the Iterative Proportional Scaling Procedure for Gaussian Graphical Models.
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- Journal of Computational & Graphical Statistics, 2015, v. 24, n. 1, p. 205, doi. 10.1080/10618600.2014.900499
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- Article
Visualizing Complex Data With Embedded Plots.
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- Journal of Computational & Graphical Statistics, 2015, v. 24, n. 1, p. 26, doi. 10.1080/10618600.2014.896808
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Graphical Models for Ordinal Data.
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- Journal of Computational & Graphical Statistics, 2015, v. 24, n. 1, p. 183, doi. 10.1080/10618600.2014.889023
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A Graphical Goodness-of-Fit Test for Dependence Models in Higher Dimensions.
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- Journal of Computational & Graphical Statistics, 2014, v. 23, n. 3, p. 700, doi. 10.1080/10618600.2013.812518
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Graphical Aids for the Analysis of Two-Level Nonregular Designs.
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- Journal of Computational & Graphical Statistics, 2014, v. 23, n. 3, p. 678, doi. 10.1080/10618600.2013.809314
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- Article
Efficient Bayesian Inference for Multivariate Probit Models With Sparse Inverse Correlation Matrices.
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- Journal of Computational & Graphical Statistics, 2012, v. 21, n. 3, p. 739, doi. 10.1080/10618600.2012.679239
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- Article
An Improved Iterative Proportional Scaling Procedure for Gaussian Graphical Models.
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- Journal of Computational & Graphical Statistics, 2011, v. 20, n. 2, p. 417, doi. 10.1198/jcgs.2010.09044
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Computational Aspects Related to Inference in Gaussian Graphical Models With the G-Wishart Prior.
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- Journal of Computational & Graphical Statistics, 2011, v. 20, n. 1, p. 140, doi. 10.1198/jcgs.2010.08181
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Enumerating the Junction Trees of a Decomposable Graph.
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- Journal of Computational & Graphical Statistics, 2009, v. 18, n. 4, p. 930, doi. 10.1198/jcgs.2009.07129
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- Article