Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

27 February 2013

Papers citing "Learning Bayesian Networks: The Combination of Knowledge and Statistical Data"

50 / 366 papers shown

Title
On the Role of Priors in Bayesian Causal Learning Bernhard C. Geiger Roman Kern CML 32 0 0 02 Apr 2025
Stable Structure Learning with HC-Stable and Tabu-Stable Algorithms N. K. Kitson Anthony C. Constantinou 39 0 0 02 Apr 2025
Heterogeneous Causal Discovery of Repeated Undesirable Health Outcomes Shishir Adhikari Guido Muscioni Mark Shapiro Plamen Petrov Elena Zheleva CML 60 0 0 14 Mar 2025
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
Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search Jorge D. Laborda Pablo Torrijos J. M. Puerta J. A. Gamez 42 0 0 03 Feb 2025
FedGES: A Federated Learning Approach for BN Structure Learning Pablo Torrijos J. A. Gamez J. M. Puerta FedML 69 1 0 03 Feb 2025
Causal Discovery via Bayesian Optimization Bao Duong Sunil Gupta Thin Nguyen 39 0 0 28 Jan 2025
Integrating Probabilistic Trees and Causal Networks for Clinical and Epidemiological Data Sheresh Zahoor Pietro Liò G. Dias Mohammed Hasanuzzaman 39 0 0 28 Jan 2025
Regularized Multi-LLMs Collaboration for Enhanced Score-based Causal Discovery Xiaoxuan Li Yao Liu Ruoyu Wang Lina Yao 65 0 0 27 Nov 2024
$ψ$ DAG: Projected Stochastic Approximation Iteration for DAG Structure Learning Klea Ziu Slavomír Hanzely Loka Li Kun Zhang Martin Takáč Dmitry Kamzolov 38 1 0 31 Oct 2024
Markov Equivalence and Consistency in Differentiable Structure Learning Chang Deng Kevin Bello Pradeep Ravikumar Bryon Aragam CML 24 0 0 08 Oct 2024
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery Yingyu Lin Yuxing Huang Wenqin Liu Haoran Deng Ignavier Ng Kun Zhang Mingming Gong Yi-An Ma Biwei Huang 25 1 0 08 Oct 2024
Choosing DAG Models Using Markov and Minimal Edge Count in the Absence of Ground Truth Joseph Ramsey Bryan Andrews Peter Spirtes CML 24 2 0 30 Sep 2024
bnRep: A repository of Bayesian networks from the academic literature Manuele Leonelli 14 2 0 27 Sep 2024
CURATE: Scaling-up Differentially Private Causal Graph Discovery Payel Bhattacharjee Ravi Tandon 16 0 0 27 Sep 2024
A Ring-Based Distributed Algorithm for Learning High-Dimensional Bayesian Networks Jorge D. Laborda Pablo Torrijos J. M. Puerta J. A. Gamez 14 2 0 20 Sep 2024
Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures T. Silander Janne Leppä-aho Elias Jääsaari Teemu Roos 34 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 29 0 0 20 Aug 2024
Kernel-Based Differentiable Learning of Non-Parametric Directed Acyclic Graphical Models Yurou Liang Oleksandr Zadorozhnyi Mathias Drton CML 31 0 0 20 Aug 2024
Bayesian Network Modeling of Causal Influence within Cognitive Domains and Clinical Dementia Severity Ratings for Western and Indian Cohorts Wupadrasta Santosh Kumar Sayali Rajendra Bhutare Neelam Sinha T. Issac CML 18 0 0 16 Aug 2024
From Pre-training Corpora to Large Language Models: What Factors Influence LLM Performance in Causal Discovery Tasks? Tao Feng Lizhen Qu Niket Tandon Zhuang Li Xiaoxi Kang Gholamreza Haffari LRM 27 4 0 29 Jul 2024
An Efficient Procedure for Computing Bayesian Network Structure Learning Hongming Huang Joe Suzuki 16 0 0 24 Jul 2024
Scalable Variational Causal Discovery Unconstrained by Acyclicity Nu Hoang Bao Duong Thin Nguyen CML 39 0 0 06 Jul 2024
Learnability of Parameter-Bounded Bayes Nets Arnab Bhattacharyya Davin Choo Sutanu Gayen Dimitrios Myrisiotis 23 0 0 01 Jul 2024
Learning Dynamic Bayesian Networks from Data: Foundations, First Principles and Numerical Comparisons Vyacheslav Kungurtsev Fadwa Idlahcen Petr Rysavý Pavel Rytír Ales Wodecki 45 1 0 25 Jun 2024
Greedy equivalence search for nonparametric graphical models Bryon Aragam CML 22 1 0 25 Jun 2024
Causality-based Transfer of Driving Scenarios to Unseen Intersections C. Glasmacher Michael Schuldes Sleiman El Masri Lutz Eckstein 27 0 0 02 Apr 2024
Recursive Causal Discovery Ehsan Mokhtarian Sepehr Elahi S. Akbari Negar Kiyavash CML 30 0 0 14 Mar 2024
Towards Automated Causal Discovery: a case study on 5G telecommunication data Konstantina Biza Antonios Ntroumpogiannis Sofia Triantafillou Ioannis Tsamardinos 28 0 0 22 Feb 2024
Causal Discovery under Off-Target Interventions Davin Choo Kirankumar Shiragur Caroline Uhler CML 20 1 1 13 Feb 2024
Graph Neural Machine: A New Model for Learning with Tabular Data Giannis Nikolentzos Siyun Wang J. Lutzeyer Michalis Vazirgiannis 24 0 0 05 Feb 2024
Building Expressive and Tractable Probabilistic Generative Models: A Review Sahil Sidheekh S. Natarajan TPM 11 5 0 01 Feb 2024
Personalized Decision Supports based on Theory of Mind Modeling and Explainable Reinforcement Learning Huao Li Yao Fan Keyang Zheng Michael Lewis Katia P. Sycara 20 0 0 13 Dec 2023
Bayesian causal discovery from unknown general interventions Alessandro Mascaro F. Castelletti 8 1 0 01 Dec 2023
Entropy and the Kullback-Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation Marco Scutari 6 2 0 29 Nov 2023
Applying Large Language Models for Causal Structure Learning in Non Small Cell Lung Cancer Narmada Naik Ayush Khandelwal Mohit Joshi Madhusudan Atre Hollis Wright ... Giridhar Mamidipudi Ganapati Srinivasa Carlo Bifulco B. Piening Kevin Matlock 112 11 0 13 Nov 2023
Extracting the Multiscale Causal Backbone of Brain Dynamics Gabriele DÁcunto Francesco Bonchi G. D. F. Morales Giovanni Petri 11 0 0 31 Oct 2023
Causal discovery using dynamically requested knowledge N. K. Kitson Anthony C. Constantinou CML 4 0 0 17 Oct 2023
Fast & Efficient Learning of Bayesian Networks from Data: Knowledge Discovery and Causality Sein Minn Shunkai Fu CML BDL 13 0 0 13 Oct 2023
Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach Zhenlan Ji Pingchuan Ma Zongjie Li Shuai Wang 24 21 0 10 Oct 2023
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGs Moritz Schauer Marcel Wienöbst CML 17 2 0 09 Oct 2023
Evolutionary Retrosynthetic Route Planning Yan Zhang Hao Hao Xiao He Shuanhu Gao Aimin Zhou 11 1 0 08 Oct 2023
Shadow Datasets, New challenging datasets for Causal Representation Learning Jiageng Zhu Hanchen Xie Jianhua Wu Jiazhi Li Mahyar Khayatkhoei Mohamed E. Hussein Wael AbdAlmageed 14 2 0 10 Aug 2023
Exploring Effective Priors and Efficient Models for Weakly-Supervised Change Detection Zhenghui Zhao Lixiang Ru Chen Wu 18 6 0 20 Jul 2023
Global Optimality in Bivariate Gradient-based DAG Learning Chang Deng Kevin Bello Bryon Aragam Pradeep Ravikumar 31 8 0 30 Jun 2023
Joint structure learning and causal effect estimation for categorical graphical models F. Castelletti G. Consonni Marco L. Della Vedova CML 19 2 0 28 Jun 2023
Tuning structure learning algorithms with out-of-sample and resampling strategies Kiattikun Chobtham Anthony C. Constantinou CML 10 2 0 24 Jun 2023
Bivariate Causal Discovery using Bayesian Model Selection Anish Dhir Samuel Power Mark van der Wilk CML 15 3 0 05 Jun 2023
Active causal structure learning with advice Davin Choo Themis Gouleakis Arnab Bhattacharyya CML 32 3 0 31 May 2023
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network T. Deleu Mizu Nishikawa-Toomey Jithendaraa Subramanian Nikolay Malkin Laurent Charlin Yoshua Bengio BDL 28 43 0 30 May 2023