A Transformational Characterization of Equivalent Bayesian Network Structures

20 February 2013

Papers citing "A Transformational Characterization of Equivalent Bayesian Network Structures"

50 / 98 papers shown

Title
Heterogeneous Causal Discovery of Repeated Undesirable Health Outcomes Shishir Adhikari Guido Muscioni Mark Shapiro Plamen Petrov Elena Zheleva CML 58 0 0 14 Mar 2025
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions Juan L. Gamella Armeen Taeb C. Heinze-Deml Peter Buhlmann CML 81 7 0 13 Mar 2025
Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures T. Silander Janne Leppä-aho Elias Jääsaari Teemu Roos 29 27 0 27 Aug 2024
A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders Christophe Gonzales Amir-Hosein Valizadeh BDL CML 24 0 0 20 Aug 2024
Causal Discovery with Fewer Conditional Independence Tests Kirankumar Shiragur Jiaqi Zhang Caroline Uhler CML 23 1 0 03 Jun 2024
The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology Juan L. Gamella Jonas Peters Peter Buhlmann 75 8 0 17 Apr 2024
Colored Gaussian DAG models Tobias Boege Kaie Kubjas Pratik Misra Liam Solus 45 0 0 05 Apr 2024
Membership Testing in Markov Equivalence Classes via Independence Query Oracles Jiaqi Zhang Kirankumar Shiragur Caroline Uhler CML 43 0 0 09 Mar 2024
Causal Discovery under Off-Target Interventions Davin Choo Kirankumar Shiragur Caroline Uhler CML 13 1 1 13 Feb 2024
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables Xinshuai Dong Biwei Huang Ignavier Ng Xiangchen Song Yujia Zheng Songyao Jin Roberto Legaspi Peter Spirtes Kun Zhang BDL CML 11 10 0 18 Dec 2023
Bayesian causal discovery from unknown general interventions Alessandro Mascaro F. Castelletti 8 1 0 01 Dec 2023
Extracting the Multiscale Causal Backbone of Brain Dynamics Gabriele DÁcunto Francesco Bonchi G. D. F. Morales Giovanni Petri 9 0 0 31 Oct 2023
Meek Separators and Their Applications in Targeted Causal Discovery Kirankumar Shiragur Jiaqi Zhang Caroline Uhler CML 21 2 0 30 Oct 2023
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow-Shrink Trees Bryan Andrews Joseph Ramsey Ruben Sanchez-Romero Jazmin Camchong Erich Kummerfeld CML 10 16 0 26 Oct 2023
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGs Moritz Schauer Marcel Wienöbst CML 12 2 0 09 Oct 2023
A Fixed-Parameter Tractable Algorithm for Counting Markov Equivalence Classes with the same Skeleton Vidya Sagar Sharma 19 0 0 06 Oct 2023
Learning nonparametric latent causal graphs with unknown interventions Yibo Jiang Bryon Aragam CML 24 24 0 05 Jun 2023
Positivity in Linear Gaussian Structural Equation Models A. Lodhia Jan-Christian Hütter Caroline Uhler Piotr Zwiernik 17 1 0 31 May 2023
Active causal structure learning with advice Davin Choo Themis Gouleakis Arnab Bhattacharyya CML 25 3 0 31 May 2023
New metrics and search algorithms for weighted causal DAGs Davin Choo Kirankumar Shiragur CML 14 1 0 08 May 2023
Practical Algorithms for Orientations of Partially Directed Graphical Models Malte Luttermann Marcel Wienöbst Maciej Liskiewicz CML 14 1 0 28 Feb 2023
Causal Razors Wai-yin Lam CML 14 0 0 20 Feb 2023
Efficient Enumeration of Markov Equivalent DAGs Marcel Wienöbst Malte Luttermann Max Bannach Maciej Liskiewicz 20 5 0 28 Jan 2023
Subset verification and search algorithms for causal DAGs Davin Choo Kirankumar Shiragur CML 11 10 0 09 Jan 2023
Verification and search algorithms for causal DAGs Davin Choo Kirankumar Shiragur Arnab Bhattacharyya CML 11 10 0 30 Jun 2022
Counting Markov Equivalent Directed Acyclic Graphs Consistent with Background Knowledge Vidya Sagar Sharma 20 0 0 14 Jun 2022
Greedy Relaxations of the Sparsest Permutation Algorithm Wai-yin Lam Bryan Andrews Joseph Ramsey 17 43 0 11 Jun 2022
Causal Structure Learning: a Combinatorial Perspective C. Squires Caroline Uhler CML 12 46 0 02 Jun 2022
Fast Causal Orientation Learning in Directed Acyclic Graphs Ramin Safaeian Saber Salehkaleybar M. Tabandeh CML 15 2 0 27 May 2022
Gaussian mixture modeling of nodes in Bayesian network according to maximal parental cliques Yiran Dong Chuanhou Gao 11 0 0 20 Apr 2022
A Transformational Characterization of Unconditionally Equivalent Bayesian Networks Alex Markham Danai Deligeorgaki Pratik Misra Liam Solus 14 2 0 01 Mar 2022
Causal KL: Evaluating Causal Discovery R. T. O'Donnell K. Korb L. Allison CML 12 2 0 11 Nov 2021
Universal Lower Bound for Learning Causal DAGs with Atomic Interventions Vibhor Porwal P. Srivastava Gaurav Sinha CML 15 2 0 09 Nov 2021
Benchpress: A Scalable and Versatile Workflow for Benchmarking Structure Learning Algorithms Felix L. Rios G. Moffa Jack Kuipers CML 22 12 0 08 Jul 2021
Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions D. Geiger David Heckerman 109 195 0 05 May 2021
Greedy Causal Discovery is Geometric Svante Linusson Petter Restadh Liam Solus CML 16 9 0 05 Mar 2021
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game Alexander G. Reisach C. Seiler S. Weichwald CML 10 136 0 26 Feb 2021
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes Quan Zhou Hyunwoong Chang 79 12 0 11 Jan 2021
The FEDHC Bayesian network learning algorithm M. Tsagris 11 3 0 30 Nov 2020
Towards Scalable Bayesian Learning of Causal DAGs Jussi Viinikka Antti Hyttinen J. Pensar Mikko Koivisto CML 17 34 0 30 Sep 2020
A Bayesian Hierarchical Score for Structure Learning from Related Data Sets Laura Azzimonti Giorgio Corani M. Scutari 11 6 0 04 Aug 2020
Learning DAGs without imposing acyclicity Gherardo Varando CML 17 12 0 04 Jun 2020
Learning Bayesian Networks from Incomplete Data with the Node-Average Likelihood T. Bodewes M. Scutari 11 6 0 29 Apr 2020
Causal datasheet: An approximate guide to practically assess Bayesian networks in the real world B. Butcher V. Huang Jeremy Reffin S. Sgaier Grace Charles Novi Quadrianto CML 11 17 0 12 Mar 2020
A Tutorial on Learning With Bayesian Networks David Heckerman CML 16 3,513 0 01 Feb 2020
Ordering-Based Causal Structure Learning in the Presence of Latent Variables D. Bernstein Basil Saeed C. Squires Caroline Uhler CML 19 40 0 20 Oct 2019
Towards Characterising Bayesian Network Models under Selection A. Armen R. Evans CML 14 1 0 13 Nov 2018
Who Learns Better Bayesian Network Structures: Accuracy and Speed of Structure Learning Algorithms M. Scutari C. E. Graafland J. Gutiérrez CML 20 53 0 30 May 2018
Learning Bayesian Networks from Big Data with Greedy Search: Computational Complexity and Efficient Implementation M. Scutari C. Vitolo A. Tucker 15 24 0 22 Apr 2018
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs Diviyan Kalainathan Olivier Goudet Isabelle M Guyon David Lopez-Paz Michèle Sebag CML 11 93 0 13 Mar 2018