Learning Bayesian Networks with the bnlearn R Package

26 August 2009

Papers citing "Learning Bayesian Networks with the bnlearn R Package"

48 / 48 papers shown

Title
SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph Mátyás Schubert Tom Claassen Sara Magliacane CML 71 0 0 11 Feb 2025
bnRep: A repository of Bayesian networks from the academic literature Manuele Leonelli 14 2 0 27 Sep 2024
Adaptive Online Experimental Design for Causal Discovery Muhammad Qasim Elahi Lai Wei Murat Kocaoglu Mahsa Ghasemi CML 36 1 0 19 May 2024
Generating Likely Counterfactuals Using Sum-Product Networks Jiri Nemecek Tomás Pevný Jakub Marecek TPM 65 0 0 25 Jan 2024
Learning Bayesian Networks with Heterogeneous Agronomic Data Sets via Mixed-Effect Models and Hierarchical Clustering Lorenzo Valleggi M. Scutari F. Stefanini 17 2 0 11 Aug 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 62 9 0 19 Jun 2023
A Survey on Causal Discovery: Theory and Practice Alessio Zanga Fabio Stella CML 21 37 0 17 May 2023
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data Uzma Hasan Emam Hossain Md. Osman Gani CML AI4TS 23 24 0 27 Mar 2023
Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear Manuele Leonelli Gherardo Varando CML 16 6 0 02 Jan 2023
Fast Parallel Bayesian Network Structure Learning Jiantong Jiang Zeyi Wen Ajmal Saeed Mian 22 6 0 08 Dec 2022
$Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery$ Trust Your $\nabla$ : Gradient-based Intervention Targeting for Causal Discovery Mateusz Olko Michal Zajac A. Nowak Nino Scherrer Yashas Annadani Stefan Bauer Lukasz Kucinski Piotr Milos CML 22 2 0 24 Nov 2022
cegpy: Modelling with Chain Event Graphs in Python G. Walley Aditi Shenvi P. Strong Katarzyna Kobalczyk 8 6 0 21 Nov 2022
Membership Inference Attacks and Generalization: A Causal Perspective Teodora Baluta Shiqi Shen S. Hitarth Shruti Tople Prateek Saxena OOD MIACV 34 18 0 18 Sep 2022
A Causal-based Approach to Explain, Predict and Prevent Failures in Robotic Tasks Maximilian Diehl Karinne Ramirez-Amaro CML 31 21 0 12 Sep 2022
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies Adam Thelen Xiaoge Zhang Olga Fink Yan Lu Sayan Ghosh B. Youn Michael D. Todd S. Mahadevan Chao Hu Zhen Hu SyDa AI4CE 21 187 0 26 Aug 2022
Highly Efficient Structural Learning of Sparse Staged Trees Manuele Leonelli Gherardo Varando 10 13 0 14 Jun 2022
Causal Discovery for Fairness Ruta Binkyt.e-Sadauskien.e K. Makhlouf Carlos Pinzón Sami Zhioua C. Palamidessi CML 9 16 0 14 Jun 2022
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs Zehao Dong Muhan Zhang Fuhai Li Yixin Chen CML GNN 25 17 0 19 Mar 2022
Distributed Learning of Generalized Linear Causal Networks Qiaoling Ye Arash A. Amini Qing Zhou CML OOD AI4CE 25 16 0 23 Jan 2022
Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers Wei Zhou Xin He Wei Zhong Junhui Wang CML 25 4 0 01 Nov 2021
ParaLiNGAM: Parallel Causal Structure Learning for Linear non-Gaussian Acyclic Models Amirhossein Shahbazinia Saber Salehkaleybar Matin Hashemi CML 33 7 0 28 Sep 2021
A survey of Bayesian Network structure learning N. K. Kitson Anthony C. Constantinou Zhi-gao Guo Yang Liu Kiattikun Chobtham CML 18 181 0 23 Sep 2021
A Fast PC Algorithm with Reversed-order Pruning and A Parallelization Strategy Kai Zhang Chao Tian Kun Zhang Todd Johnson Xiaoqian Jiang CML 35 4 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 16 1 0 16 Aug 2021
Staged trees and asymmetry-labeled DAGs Gherardo Varando Federico Carli Manuele Leonelli 11 12 0 04 Aug 2021
Learning complex dependency structure of gene regulatory networks from high dimensional micro-array data with Gaussian Bayesian networks C. E. Graafland J. Gutiérrez 21 4 0 28 Jun 2021
Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning Zhaolong Ling Kui Yu Yiwen Zhang Lin Liu Jiuyong Li CML 23 28 0 11 Mar 2021
Towards Scalable Bayesian Learning of Causal DAGs Jussi Viinikka Antti Hyttinen J. Pensar Mikko Koivisto CML 22 34 0 30 Sep 2020
Causal Discovery from Incomplete Data: A Deep Learning Approach Yuhao Wang Vlado Menkovski Hao Wang Xin Du Mykola Pechenizkiy CML 23 34 0 15 Jan 2020
Causality-based Feature Selection: Methods and Evaluations Kui Yu Xianjie Guo Lin Liu Jiuyong Li Hao Wang Zhaolong Ling Xindong Wu CML 16 92 0 17 Nov 2019
Alleviating Privacy Attacks via Causal Learning Shruti Tople Amit Sharma A. Nori MIACV OOD 14 32 0 27 Sep 2019
missSBM: An R Package for Handling Missing Values in the Stochastic Block Model P. Barbillon J. Chiquet Timothée Tabouy 8 2 0 28 Jun 2019
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs Muhan Zhang Shali Jiang Zhicheng Cui Roman Garnett Yixin Chen GNN BDL CML 16 196 0 24 Apr 2019
Testing Conditional Independence in Supervised Learning Algorithms David S. Watson Marvin N. Wright CML 24 52 0 28 Jan 2019
A geometric characterisation of sensitivity analysis in monomial models Manuele Leonelli Eva Riccomagno 21 13 0 18 Dec 2018
Who Learns Better Bayesian Network Structures: Accuracy and Speed of Structure Learning Algorithms M. Scutari C. E. Graafland J. Gutiérrez CML 28 53 0 30 May 2018
Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks Alex E. White Matthieu Vignes CML 10 5 0 04 May 2018
Learning Bayesian Networks from Big Data with Greedy Search: Computational Complexity and Efficient Implementation M. Scutari C. Vitolo A. Tucker 20 99 0 22 Apr 2018
Efficient Sampling and Structure Learning of Bayesian Networks Jack Kuipers Polina Suter G. Moffa TPM CML 13 69 0 21 Mar 2018
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs Diviyan Kalainathan Olivier Goudet Isabelle M Guyon David Lopez-Paz Michèle Sebag CML 16 93 0 13 Mar 2018
Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena Daniele Ramazzotti Marco S. Nobile M. Antoniotti Alex Graudenzi CML 9 4 0 08 Mar 2017
Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks S. Beretta M. Castelli Ivo Gonçalves I. Merelli Daniele Ramazzotti 16 2 0 08 Mar 2017
High-dimensional consistency in score-based and hybrid structure learning Preetam Nandy Alain Hauser Marloes H. Maathuis 39 128 0 09 Jul 2015
A hybrid algorithm for Bayesian network structure learning with application to multi-label learning Maxime Gasse A. Aussem H. Elghazel 19 88 0 18 Jun 2015
A fast PC algorithm for high dimensional causal discovery with multi-core PCs T. Le Tao Hoang Jiuyong Li Lin Liu Huawen Liu 26 139 0 09 Feb 2015
Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel and Optimised Implementations in the bnlearn R Package M. Scutari CML 49 164 0 30 Jun 2014
A Transformational Characterization of Equivalent Bayesian Network Structures D. M. Chickering 151 416 0 20 Feb 2013
On Identifying Significant Edges in Graphical Models of Molecular Networks M. Scutari R. Nagarajan 57 167 0 05 Apr 2011