Structure Learning in Graphical Modeling

7 June 2016

Papers citing "Structure Learning in Graphical Modeling"

50 / 102 papers shown

Title
Interaction Models and Generalized Score Matching for Compositional DataLOG IN (LOG IN), 2021 Shiqing Yu Mathias Drton Ali Shojaie 115 2 0 10 Sep 2021
WiseR: An end-to-end structure learning and deployment framework for causal graphical models Shubham Maheshwari Khushbu Pahwa Tavpritesh Sethi CML 249 1 0 16 Aug 2021
Learning Linear Polytree Structural Equation Models Xingmei Lou Yu Hu Xiaodong Li CML 304 1 0 22 Jul 2021
Prequential MDL for Causal Structure Learning with Neural Networks J. Bornschein Silvia Chiappa Alan Malek Rosemary Nan Ke CML 188 2 0 02 Jul 2021
Bayesian structure learning and sampling of Bayesian networks with the R package BiDAGJournal of Statistical Software (JSS), 2021 Polina Suter Jack Kuipers G. Moffa N. Beerenwinkel 113 49 0 02 May 2021
Batch Bayesian Optimization on Permutations using the Acquisition Weighted KernelNeural Information Processing Systems (NeurIPS), 2021 Changyong Oh Roberto Bondesan E. Gavves Max Welling 166 15 0 26 Feb 2021
Estimating a Directed Tree for Extremes N. Tran Johannes Buck Claudia Klüppelberg 248 12 0 11 Feb 2021
Gaussian Experts Selection using Graphical Models Hamed Jalali Martin Pawelczyk Gjerji Kasneci 176 3 0 02 Feb 2021
How do some Bayesian Network machine learned graphs compare to causal knowledge? Anthony C. Constantinou Norman E. Fenton M. Neil CML 205 3 0 25 Jan 2021
Learning and scoring Gaussian latent variable causal models with unknown additive interventions Armeen Taeb Juan L. Gamella C. Heinze-Deml Peter Buhlmann CML 538 3 0 18 Jan 2021
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classesAnnals of Statistics (Ann. Stat.), 2021 Quan Zhou Hyunwoong Chang 317 15 0 11 Jan 2021
Learning non-Gaussian graphical models via Hessian scores and triangular transportJournal of machine learning research (JMLR), 2021 Ricardo Baptista Youssef Marzouk Rebecca E. Morrison O. Zahm 277 26 0 08 Jan 2021
Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications Rong Zhu A. Pfadler Ziniu Wu Yuxing Han Xiaoke Yang Feng Ye Zhenping Qian Jingren Zhou Tengjiao Wang 241 11 0 07 Dec 2020
Limits on Testing Structural Changes in Ising Models Aditya Gangrade B. Nazer Venkatesh Saligrama 202 0 0 07 Nov 2020
Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control Sai Li T. Tony Cai Hongzhe Li 204 72 0 21 Oct 2020
Aggregating Dependent Gaussian Experts in Local ApproximationInternational Conference on Pattern Recognition (ICPR), 2020 Hamed Jalali Gjergji Kasneci 150 4 0 17 Oct 2020
Causal learning with sufficient statistics: an information bottleneck approach D. Chicharro M. Besserve S. Panzeri CML 150 5 0 12 Oct 2020
Efficient least squares for estimating total effects under linearity and causal sufficiencyJournal of machine learning research (JMLR), 2020 By F. Richard Guo Emilija Perković CML 341 13 0 08 Aug 2020
Consistent Second-Order Conic Integer Programming for Learning Bayesian NetworksJournal of machine learning research (JMLR), 2020 Simge Küçükyavuz Ali Shojaie Hasan Manzour Linchuan Wei Hao-Hsiang Wu 299 19 0 29 May 2020
Sparse Structures for Multivariate ExtremesAnnual Review of Statistics and Its Application (ARSIA), 2020 Sebastian Engelke J. Ivanovs 224 86 0 25 Apr 2020
Differential Network Analysis: A Statistical Perspective Ali Shojaie 250 54 0 09 Mar 2020
Multi-trek separation in Linear Structural Equation ModelsSIAM Journal on applied algebra and geometry (JSAAG), 2020 Elina Robeva Jean-Baptiste Seby CML 288 12 0 28 Jan 2020
Human-like Time Series Summaries via Trend Utility Estimation Pegah Jandaghi Jay Pujara AI4TS 162 1 0 16 Jan 2020
Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble MethodInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Pengzhou (Abel) Wu Kenji Fukumizu CML 195 27 0 07 Jan 2020
Graph quilting: graphical model selection from partially observed covariances Giuseppe Vinci Gautam Dasarathy Genevera I. Allen CML 327 22 0 11 Dec 2019
Direct Estimation of Differential Functional Graphical ModelsNeural Information Processing Systems (NeurIPS), 2019 Boxin Zhao Y Samuel Wang Mladen Kolar 179 15 0 22 Oct 2019
Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity Sen Na Mladen Kolar Oluwasanmi Koyejo 155 26 0 12 Sep 2019
Certifiably Optimal Sparse Inverse Covariance EstimationMathematical programming (Math. Program.), 2019 Dimitris Bertsimas Jourdain Lamperski J. Pauphilet 154 14 0 25 Jun 2019
Learning partial correlation graphs and graphical models by covariance queriesJournal of machine learning research (JMLR), 2019 Gábor Lugosi J. Truszkowski Vasiliki Velona Piotr Zwiernik 215 6 0 22 Jun 2019
On Testing Marginal versus Conditional Independence F. R. Guo Thomas S. Richardson 222 5 0 05 Jun 2019
Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity NetworksBiometrics (Biometrics), 2019 Kean Ming Tan Junwei Lu Tong Zhang Han Liu 123 1 0 28 May 2019
Conditionally-additive-noise Models for Structure Learning D. Chicharro S. Panzeri I. Shpitser CML 154 4 0 20 May 2019
Learning Clique Forests Guido Previde Massara T. Aste 192 17 0 06 May 2019
Integer Programming for Learning Directed Acyclic Graphs from Continuous Data Hasan Manzour Simge Küçükyavuz Ali Shojaie CML 152 41 0 23 Apr 2019
Generalized Score Matching for Non-Negative Data Shiqing Yu Mathias Drton Ali Shojaie 256 2 0 26 Dec 2018
Predictive Learning on Hidden Tree-Structured Ising Models Konstantinos E. Nikolakakis Dionysios S. Kalogerias Anand D. Sarwate 429 14 0 11 Dec 2018
Graphical Models for Extremes Sebastian Engelke Adrien Hitz 317 125 0 04 Dec 2018
Joint Nonparametric Precision Matrix Estimation with Confounding Sinong Geng Mladen Kolar Oluwasanmi Koyejo 182 9 0 16 Oct 2018
Algebraic Equivalence of Linear Structural Equation Models T. V. Ommen Joris M. Mooij 177 5 0 10 Jul 2018
On Causal Discovery with Equal Variance Assumption Wenyu Chen Mathias Drton Y Samuel Wang CML 347 96 0 09 Jul 2018
On the Properties of MVR Chain Graphs Mohammad Ali Javidian Marco Valtorta 314 6 0 09 Mar 2018
Inference in high-dimensional graphical models Jana Janková Sara van de Geer 221 68 0 25 Jan 2018
Causal Generative Neural Networks Olivier Goudet Diviyan Kalainathan Philippe Caillou Isabelle M Guyon David Lopez-Paz Michèle Sebag BDL CML DRL 173 62 0 24 Nov 2017
Model-based Clustering with Sparse Covariance Matrices Michael Fop T. B. Murphy Luca Scrucca 187 42 0 21 Nov 2017
Learning Functional Causal Models with Generative Neural Networks Hugo Jair Escalante Sergio Escalera Xavier Baro Isabelle M Guyon Umut Güçlü Marcel van Gerven CML BDL 358 110 0 15 Sep 2017
High-Dimensional Dependency Structure Learning for Physical Processes Jamal Golmohammadi I. Ebert‐Uphoff Sijie He Yi Deng A. Banerjee AI4CE 109 0 0 12 Sep 2017
Graphical Nonconvex Optimization for Optimal Estimation in Gaussian Graphical ModelsInternational Conference on Machine Learning (ICML), 2017 Qiang Sun Kean Ming Tan Han Liu Tong Zhang 154 8 0 04 Jun 2017
Learning Gaussian Graphical Models Using Discriminated Hub Graphical Lasso Zerui Li Jingtian Bai Weilian Zhou 189 1 0 17 May 2017
A Review on Algorithms for Constraint-based Causal Discovery Kui Yu Jiuyong Li Lin Liu AI4TS CML 140 22 0 12 Nov 2016
Computation of maximum likelihood estimates in cyclic structural equation modelsAnnals of Statistics (Ann. Stat.), 2016 Mathias Drton C. Fox Y Samuel Wang 239 18 0 11 Oct 2016