Structure Learning in Graphical Modeling

7 June 2016

Papers citing "Structure Learning in Graphical Modeling"

42 / 42 papers shown

Title
Model-free Estimation of Latent Structure via Multiscale Nonparametric Maximum Likelihood Bryon Aragam Ruiyi Yang 45 0 0 29 Oct 2024
Discrete distributions are learnable from metastable samples Abhijith Jayakumar A. Lokhov Sidhant Misra Marc Vuffray 42 1 0 17 Oct 2024
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching Daniel J. Williams Leyang Wang Qizhen Ying Song Liu Mladen Kolar 40 1 0 14 Oct 2024
Parameter identification in linear non-Gaussian causal models under general confounding D. Tramontano Mathias Drton Jalal Etesami CML 45 1 0 31 May 2024
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models Tong Xu Armeen Taeb Simge Kuccukyavuz Ali Shojaie CML 39 1 0 19 Apr 2024
Computational Hypergraph Discovery, a Gaussian Process framework for connecting the dots Théo Bourdais Pau Batlle Xianjin Yang Ricardo Baptista Nicolas Rouquette H. Owhadi 21 0 0 28 Nov 2023
Model Selection over Partially Ordered Sets Armeen Taeb Peter Bühlmann V. Chandrasekaran 16 5 0 20 Aug 2023
Learning the hub graphical Lasso model with the structured sparsity via an efficient algorithm Chengjing Wang Peipei Tang Wen-Bin He Meixia Lin 33 0 0 17 Aug 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris C. Emezue Alexandre Drouin T. Deleu Stefan Bauer Yoshua Bengio CML 35 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 73 10 0 19 Jun 2023
The Functional Graphical Lasso Kartik G. Waghmare T. Masak V. Panaretos 14 1 0 04 Jun 2023
Maximum a Posteriori Estimation in Graphical Models Using Local Linear Approximation K. Sagar J. Datta Sayantan Banerjee A. Bhadra 24 2 0 13 Mar 2023
pyGSL: A Graph Structure Learning Toolkit Max Wasserman Gonzalo Mateos 40 0 0 07 Nov 2022
Ensemble transport smoothing. Part II: Nonlinear updates M. Ramgraber Ricardo Baptista D. McLaughlin Youssef Marzouk 31 6 0 31 Oct 2022
Learning Linear Non-Gaussian Polytree Models D. Tramontano Anthea Monod Mathias Drton 31 7 0 13 Aug 2022
Valid Inference after Causal Discovery Paula Gradu Tijana Zrnic Yixin Wang Michael I. Jordan CML 26 8 0 11 Aug 2022
Learning Graph Structure from Convolutional Mixtures Max Wasserman Saurabh Sihag Gonzalo Mateos Alejandro Ribeiro GNN CML BDL 37 6 0 19 May 2022
Order-based Structure Learning without Score Equivalence Hyunwoong Chang James Cai Quan Zhou CML OffRL 29 3 0 10 Feb 2022
Distributed Learning of Generalized Linear Causal Networks Qiaoling Ye Arash A. Amini Qing Zhou CML OOD AI4CE 38 16 0 23 Jan 2022
Joint Gaussian Graphical Model Estimation: A Survey Katherine Tsai Oluwasanmi Koyejo Mladen Kolar CML 41 20 0 19 Oct 2021
Decentralized Learning of Tree-Structured Gaussian Graphical Models from Noisy Data Akram Hussain 38 0 0 22 Sep 2021
WiseR: An end-to-end structure learning and deployment framework for causal graphical models Shubham Maheshwari Khushbu Pahwa Tavpritesh Sethi CML 19 1 0 16 Aug 2021
Estimating a Directed Tree for Extremes N. Tran Johannes Buck Claudia Klüppelberg 27 8 0 11 Feb 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 18 9 0 07 Dec 2020
Differential Network Analysis: A Statistical Perspective Ali Shojaie 43 48 0 09 Mar 2020
Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method Pengzhou (Abel) Wu Kenji Fukumizu CML 27 26 0 07 Jan 2020
Direct Estimation of Differential Functional Graphical Models Boxin Zhao Y Samuel Wang Mladen Kolar 21 15 0 22 Oct 2019
Certifiably Optimal Sparse Inverse Covariance Estimation Dimitris Bertsimas Jourdain Lamperski J. Pauphilet 22 13 0 25 Jun 2019
On Testing Marginal versus Conditional Independence F. R. Guo Thomas S. Richardson 72 5 0 05 Jun 2019
Conditionally-additive-noise Models for Structure Learning D. Chicharro S. Panzeri I. Shpitser CML 11 4 0 20 May 2019
Predictive Learning on Hidden Tree-Structured Ising Models Konstantinos E. Nikolakakis Dionysios S. Kalogerias Anand D. Sarwate 23 12 0 11 Dec 2018
Graphical Models for Extremes Sebastian Engelke Adrien Hitz 24 110 0 04 Dec 2018
Algebraic Equivalence of Linear Structural Equation Models T. V. Ommen Joris M. Mooij 32 5 0 10 Jul 2018
On Causal Discovery with Equal Variance Assumption Wenyu Chen Mathias Drton Y Samuel Wang CML 22 84 0 09 Jul 2018
Model-based Clustering with Sparse Covariance Matrices Michael Fop T. B. Murphy Luca Scrucca 34 39 0 21 Nov 2017
Computation of maximum likelihood estimates in cyclic structural equation models Mathias Drton C. Fox Y Samuel Wang 27 16 0 11 Oct 2016
Graphical Models for Discrete and Continuous Data Rui Zhuang Noah Simon Johannes Lederer 13 4 0 18 Sep 2016
Robust estimators for non-decomposable elliptical graphical models D. Vogel David E. Tyler 48 11 0 21 Feb 2013
Causal Inference in the Presence of Latent Variables and Selection Bias Peter Spirtes Christopher Meek Thomas S. Richardson CML 147 438 0 20 Feb 2013
A Discovery Algorithm for Directed Cyclic Graphs Thomas S. Richardson CML 88 193 0 13 Feb 2013
Discovering Graphical Granger Causality Using the Truncating Lasso Penalty Ali Shojaie George Michailidis CML 77 214 0 03 Jul 2010
Time Varying Undirected Graphs Shuheng Zhou John D. Lafferty Larry A. Wasserman 116 240 0 20 Feb 2008