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"

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Title
Distributed Learning of Generalized Linear Causal Networks Qiaoling Ye Arash A. Amini Qing Zhou CML OOD AI4CE 25 16 0 23 Jan 2022
Ordinal Causal Discovery Yang Ni Bani Mallick CML 19 2 0 19 Jan 2022
Efficiently Disentangle Causal Representations Yuanpeng Li Joel Hestness Mohamed Elhoseiny Liang Zhao Kenneth Ward Church OOD CML 11 1 0 06 Jan 2022
Hybrid Bayesian network discovery with latent variables by scoring multiple interventions Kiattikun Chobtham Anthony C. Constantinou N. K. Kitson BDL 14 3 0 20 Dec 2021
Effective and efficient structure learning with pruning and model averaging strategies Anthony C. Constantinou Yang Liu N. K. Kitson Kiattikun Chobtham Zhi-gao Guo 13 17 0 01 Dec 2021
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks Robert Lieck M. Rohrmeier BDL 17 5 0 02 Nov 2021
Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers Wei Zhou Xin He Wei Zhong Junhui Wang CML 27 4 0 01 Nov 2021
Efficient, Anytime Algorithms for Calibration with Isotonic Regression under Strictly Convex Losses Kaan Gokcesu Hakan Gokcesu 12 5 0 31 Oct 2021
CausalAF: Causal Autoregressive Flow for Safety-Critical Driving Scenario Generation Wenhao Ding Hao-ming Lin Bo-wen Li Ding Zhao 16 28 0 26 Oct 2021
Efficient Bayesian network structure learning via local Markov boundary search Ming Gao Bryon Aragam 27 17 0 12 Oct 2021
Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families Goutham Rajendran Bohdan Kivva Ming Gao Bryon Aragam 21 17 0 10 Oct 2021
A survey of Bayesian Network structure learning N. K. Kitson Anthony C. Constantinou Zhi-gao Guo Yang Liu Kiattikun Chobtham CML 24 181 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 38 4 0 10 Sep 2021
Learning Neural Causal Models with Active Interventions Nino Scherrer O. Bilaniuk Yashas Annadani Anirudh Goyal Patrick Schwab Bernhard Schölkopf Michael C. Mozer Yoshua Bengio Stefan Bauer Nan Rosemary Ke CML 28 42 0 06 Sep 2021
Optimally Efficient Sequential Calibration of Binary Classifiers to Minimize Classification Error Kaan Gokcesu Hakan Gokcesu 11 18 0 19 Aug 2021
Improving Accuracy of Permutation DAG Search using Best Order Score Search Joseph Ramsey 11 3 0 17 Aug 2021
Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package Manuele Leonelli R. Ramanathan R. L. Wilkerson 11 9 0 25 Jul 2021
Greedy structure learning from data that contain systematic missing values Yang Liu Anthony C. Constantinou 8 10 0 09 Jul 2021
Benchpress: A Scalable and Versatile Workflow for Benchmarking Structure Learning Algorithms Felix L. Rios G. Moffa Jack Kuipers CML 27 12 0 08 Jul 2021
Exact Learning Augmented Naive Bayes Classifier Shouta Sugahara M. Ueno BDL 15 30 0 07 Jul 2021
Learning Bayesian Networks through Birkhoff Polytope: A Relaxation Method Aramayis Dallakyan Mohsen Pourahmadi CML 12 2 0 04 Jul 2021
Prequential MDL for Causal Structure Learning with Neural Networks J. Bornschein Silvia Chiappa Alan Malek Rosemary Nan Ke CML 29 2 0 02 Jul 2021
Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics P. Gillot P. Parviainen CML BDL 14 3 0 01 Jul 2021
Improved Acyclicity Reasoning for Bayesian Network Structure Learning with Constraint Programming Fulya Trösser S. D. Givry G. Katsirelos 11 10 0 23 Jun 2021
DiBS: Differentiable Bayesian Structure Learning Lars Lorch Jonas Rothfuss Bernhard Schölkopf Andreas Krause 26 87 0 25 May 2021
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation Xiao Sun B. Bahmani Nikolaos N. Vlassis WaiChing Sun Yanxun Xu CML AI4CE 63 26 0 20 May 2021
Likelihoods and Parameter Priors for Bayesian Networks David Heckerman D. Geiger 14 5 0 13 May 2021
Bayesian Model Averaging for Data Driven Decision Making when Causality is Partially Known Marios Papamichalis Abhishek Ray Ilias Bilionis Karthik N. Kannan Rajiv Krishnamurthy CML 9 1 0 12 May 2021
Bayesian Structural Learning for an Improved Diagnosis of Cyber-Physical Systems Nicolas Olivain Philipp Tiefenbacher J. Kohl 16 2 0 02 Apr 2021
Active Structure Learning of Bayesian Networks in an Observational Setting Noa Ben-David Sivan Sabato 11 4 0 25 Mar 2021
Partitioned hybrid learning of Bayesian network structures Jireh Huang Qing Zhou TPM 17 8 0 22 Mar 2021
Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture Distributions Shunsuke Horii CML 11 2 0 15 Mar 2021
Causal Markov Boundaries Sofia Triantafillou Fattaneh Jabbari Gregory F. Cooper CML OOD 10 5 0 12 Mar 2021
Deep Transfer Learning for Infectious Disease Case Detection Using Electronic Medical Records Ye Ye Andrew Gu OOD 6 2 0 08 Mar 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 26 296 0 03 Mar 2021
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models Matej Zečević D. Dhami Athresh Karanam S. Natarajan Kristian Kersting CML TPM 11 32 0 20 Feb 2021
Integer Programming for Causal Structure Learning in the Presence of Latent Variables Rui Chen S. Dash Tian Gao CML 16 14 0 05 Feb 2021
The impact of prior knowledge on causal structure learning Anthony C. Constantinou Zhi-gao Guo N. K. Kitson CML 24 30 0 31 Jan 2021
How do some Bayesian Network machine learned graphs compare to causal knowledge? Anthony C. Constantinou Norman E. Fenton M. Neil CML 6 3 0 25 Jan 2021
BayesCard: Revitilizing Bayesian Frameworks for Cardinality Estimation Ziniu Wu Amir Shaikhha Rong Zhu Kai Zeng Yuxing Han Jingren Zhou BDL 9 23 0 29 Dec 2020
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs Marcel Wienöbst Max Bannach Maciej Liskiewicz TPM 8 17 0 17 Dec 2020
Hard and Soft EM in Bayesian Network Learning from Incomplete Data Andrea Ruggieri Francesco Stranieri Fabio Stella M. Scutari 14 16 0 09 Dec 2020
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 Bin Cui 16 9 0 07 Dec 2020
The FEDHC Bayesian network learning algorithm M. Tsagris 16 3 0 30 Nov 2020
A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs Manon Romain Alexandre d’Aspremont 9 5 0 05 Nov 2020
A Recursive Markov Boundary-Based Approach to Causal Structure Learning Ehsan Mokhtarian S. Akbari AmirEmad Ghassami Negar Kiyavash CML 11 17 0 10 Oct 2020
Physical System for Non Time Sequence Data Xiong Chen CML 8 0 0 07 Oct 2020
Learning All Credible Bayesian Network Structures for Model Averaging Zhenyu A. Liao Charupriya Sharma James Cussens P. V. Beek BDL 9 0 0 27 Aug 2020
Amortized learning of neural causal representations Nan Rosemary Ke Jane X. Wang Jovana Mitrović M. Szummer Danilo Jimenez Rezende CML BDL 14 17 0 21 Aug 2020
A Bayesian Hierarchical Score for Structure Learning from Related Data Sets Laura Azzimonti Giorgio Corani M. Scutari 19 6 0 04 Aug 2020