Structure Learning in Graphical Modeling

7 June 2016

Papers citing "Structure Learning in Graphical Modeling"

50 / 102 papers shown

Title
Consistent causal discovery with equal error variances: a least-squares perspective Anamitra Chaudhuri Yang Ni Anirban Bhattacharya CML 41 0 0 18 Sep 2025
Optimal structure learning and conditional independence testing Ming Gao Yuhao Wang Bryon Aragam 160 0 0 08 Jul 2025
Nonlinear Causal Discovery for Grouped DataConference on Uncertainty in Artificial Intelligence (UAI), 2025 Konstantin Göbler Tobias Windisch Mathias Drton CML 215 1 0 05 Jun 2025
A friendly introduction to triangular transport M. Ramgraber Daniel Sharp M. Le Provost Youssef Marzouk 210 0 0 27 Mar 2025
Model-free Estimation of Latent Structure via Multiscale Nonparametric Maximum Likelihood Bryon Aragam Ruiyi Yang 368 0 0 29 Oct 2024
Discrete distributions are learnable from metastable samples Abhijith Jayakumar A. Lokhov Sidhant Misra Marc Vuffray 417 2 0 17 Oct 2024
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score MatchingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Daniel J. Williams Leyang Wang Qizhen Ying Song Liu Mladen Kolar 337 2 0 14 Oct 2024
Kernel-Based Differentiable Learning of Non-Parametric Directed Acyclic Graphical ModelsEuropean Workshop on Probabilistic Graphical Models (PGM), 2024 Yurou Liang Oleksandr Zadorozhnyi Mathias Drton CML 219 0 0 20 Aug 2024
Identifying Total Causal Effects in Linear Models under Partial HomoscedasticityInternational Journal of Approximate Reasoning (IJAR), 2024 David Strieder Mathias Drton CML 140 1 0 12 Aug 2024
DC Algorithm for Estimation of Sparse Gaussian Graphical ModelsPLoS ONE (PLoS ONE), 2024 Tomokaze Shiratori Yuichi Takano 150 0 0 08 Aug 2024
Greedy equivalence search for nonparametric graphical models Bryon Aragam CML 223 3 0 25 Jun 2024
Parameter identification in linear non-Gaussian causal models under general confounding D. Tramontano Mathias Drton Jalal Etesami CML 271 3 0 31 May 2024
From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy Julian Dörfler Benito van der Zander Markus Bläser Maciej Liskiewicz LRM 249 1 0 12 May 2024
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models Tong Xu Armeen Taeb Simge Kuccukyavuz Ali Shojaie CML 386 4 0 19 Apr 2024
Graph Structure Inference with BAM: Introducing the Bilinear Attention Mechanism Philipp Froehlich Heinz Koeppl GNN 223 2 0 12 Feb 2024
Graphical models for multivariate extremes Sebastian Engelke Manuel Hentschel Michael Lalancette Frank Rottger 81 7 0 03 Feb 2024
Multiview Graph Learning with Consensus GraphIEEE Transactions on Signal and Information Processing over Networks (TSIPN), 2024 Abdullah Karaaslanli Selin Aviyente 163 3 0 24 Jan 2024
Scalable network reconstruction in subquadratic time Tiago P. Peixoto 487 5 0 02 Jan 2024
Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dotsProceedings of the National Academy of Sciences of the United States of America (PNAS), 2023 Théo Bourdais Pau Batlle Xianjin Yang Ricardo Baptista Nicolas Rouquette H. Owhadi 267 0 0 28 Nov 2023
Distributionally Robust Skeleton Learning of Discrete Bayesian NetworksNeural Information Processing Systems (NeurIPS), 2023 Yeshu Li Brian Ziebart OOD 175 1 0 10 Nov 2023
Structured Neural Networks for Density Estimation and Causal InferenceNeural Information Processing Systems (NeurIPS), 2023 Asic Q. Chen Ruian Shi Xiang Gao Ricardo Baptista Rahul G. Krishnan CML TPM 163 8 0 03 Nov 2023
Structure Learning with Adaptive Random Neighborhood Informed MCMCNeural Information Processing Systems (NeurIPS), 2023 Alberto Caron Xitong Liang Samuel Livingstone Jim Griffin 137 4 0 01 Nov 2023
Model Selection over Partially Ordered SetsProceedings of the National Academy of Sciences of the United States of America (PNAS), 2023 Armeen Taeb Peter Bühlmann V. Chandrasekaran 129 6 0 20 Aug 2023
Partial Homoscedasticity in Causal Discovery with Linear ModelsIEEE Journal on Selected Areas in Information Theory (JSAIT), 2023 June Wu Mathias Drton CML 137 5 0 17 Aug 2023
Learning the hub graphical Lasso model with the structured sparsity via an efficient algorithmJournal of Scientific Computing (J. Sci. Comput.), 2023 Chengjing Wang Peipei Tang Wen-Bin He Meixia Lin 224 2 0 17 Aug 2023
$Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities$ Interpretable Machine Learning for Discovery: Statistical Challenges \& OpportunitiesAnnual Review of Statistics and Its Application (ARSIA), 2023 Genevera I. Allen Luqin Gan Lili Zheng 199 9 0 02 Aug 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris C. Emezue Alexandre Drouin T. Deleu Stefan Bauer Yoshua Bengio CML 252 2 0 11 Jul 2023
$$\texttt{causalAssembly}$: Generating Realistic Production Data for Benchmarking Causal Discovery$ $\texttt{causalAssembly}$ : Generating Realistic Production Data for Benchmarking Causal Discovery Konstantin Göbler Tobias Windisch Mathias Drton T. Pychynski Steffen Sonntag Martin Roth CML 382 16 0 19 Jun 2023
The Functional Graphical Lasso Kartik G. Waghmare T. Masak V. Panaretos 204 3 0 04 Jun 2023
Maximum a Posteriori Estimation in Graphical Models Using Local Linear Approximation K. Sagar J. Datta Sayantan Banerjee A. Bhadra 195 3 0 13 Mar 2023
Learning Personalized Brain Functional Connectivity of MDD Patients from Multiple Sites via Federated Bayesian Networks Shuai Liu Xiao Guo S. Qi Huan Wang Xiangyu Chang FedML 163 3 0 06 Jan 2023
Robust Model Selection of Gaussian Graphical Models Abrar Zahin Rajasekhar Anguluri Lalitha Sankar O. Kosut Gautam Dasarathy 163 0 0 10 Nov 2022
pyGSL: A Graph Structure Learning Toolkit Max Wasserman Gonzalo Mateos 237 0 0 07 Nov 2022
Ensemble transport smoothing. Part II: Nonlinear updates M. Ramgraber Ricardo Baptista D. McLaughlin Youssef Marzouk 191 6 0 31 Oct 2022
Confounder Selection: Objectives and Approaches F. R. Guo A. Lundborg Qingyuan Zhao CML 234 8 0 29 Aug 2022
Learning Linear Non-Gaussian Polytree ModelsConference on Uncertainty in Artificial Intelligence (UAI), 2022 D. Tramontano Anthea Monod Mathias Drton 227 10 0 13 Aug 2022
Valid Inference after Causal DiscoveryJournal of the American Statistical Association (JASA), 2022 Paula Gradu Tijana Zrnic Yixin Wang Michael I. Jordan CML 281 13 0 11 Aug 2022
Causal Structure Learning: a Combinatorial PerspectiveFoundations of Computational Mathematics (FoCM), 2022 C. Squires Caroline Uhler CML 315 60 0 02 Jun 2022
Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens Stefano Teso Laurens Bliek Andrea Borghesi M. Lombardi Neil Yorke-Smith Tias Guns Baptiste Caramiaux 146 3 0 20 May 2022
Learning Graph Structure from Convolutional Mixtures Max Wasserman Saurabh Sihag Gonzalo Mateos Alejandro Ribeiro GNN CML BDL 144 7 0 19 May 2022
Adversarial random forests for density estimation and generative modelingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 David S. Watson Kristin Blesch Jan Kapar Marvin N. Wright GAN 286 36 0 19 May 2022
CKH: Causal Knowledge Hierarchy for Estimating Structural Causal Models from Data and PriorsAnnual International Computer Software and Applications Conference (COMPSAC), 2022 Riddhiman Adib M. Naved Chih-Hao Fang Md. Osman Gani A. Grama Paul M. Griffin Sheikh Iqbal Ahamed Mohammad Adibuzzaman 80 4 0 28 Apr 2022
Two Gaussian regularization methods for time-varying networksJournal of Agricultural Biological and Environmental Statistics (JABES), 2022 Jie Jian Peijun Sang Mu Zhu 202 1 0 14 Feb 2022
Order-based Structure Learning without Score EquivalenceBiometrika (Biometrika), 2022 Hyunwoong Chang James Cai Quan Zhou CML OffRL 268 5 0 10 Feb 2022
Gaussian Graphical Models as an Ensemble Method for Distributed Gaussian Processes Hamed Jalali Gjergji Kasneci FedML 126 0 0 07 Feb 2022
Distributed Learning of Generalized Linear Causal NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Qiaoling Ye Arash A. Amini Qing Zhou CML OOD AI4CE 189 21 0 23 Jan 2022
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian NetworksNeural Information Processing Systems (NeurIPS), 2021 Robert Lieck M. Rohrmeier BDL 190 5 0 02 Nov 2021
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles Tianyi Yao Minjie Wang Genevera I. Allen 227 1 0 22 Oct 2021
Joint Gaussian Graphical Model Estimation: A Survey Katherine Tsai Oluwasanmi Koyejo Mladen Kolar CML 334 30 0 19 Oct 2021
Decentralized Learning of Tree-Structured Gaussian Graphical Models from Noisy Data Akram Hussain 171 0 0 22 Sep 2021