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This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2023
[j12]Neville Kenneth Kitson
, Anthony C. Constantinou, Zhigao Guo, Yang Liu, Kiattikun Chobtham:
A survey of Bayesian Network structure learning. Artif. Intell. Rev. 56(8): 8721-8814 (2023)- [j11]Anthony C. Constantinou, Zhigao Guo, Neville Kenneth Kitson:
The impact of prior knowledge on causal structure learning. Knowl. Inf. Syst. 65(8): 3385-3434 (2023) - 2022
- [j10]Yongyan Hou, Ao Yang, Wenqiang Guo, Enrang Zheng, Qinkun Xiao, Zhigao Guo, Zixuan Huang:
Bearing Fault Diagnosis Under Small Data Set Condition: A Bayesian Network Method With Transfer Learning for Parameter Estimation. IEEE Access 10: 35768-35783 (2022) - [j9]Ruohai Di, Peng Wang, Jiao Wu, Zhigao Guo:
A Novel Qualitative Maximum a Posteriori Estimation for Bayesian Network Parameters Based on Computing the Center Point of Constrained Parameter Regions. IEEE Access 10: 37269-37280 (2022) - [j8]Anthony C. Constantinou, Yang Liu, Neville Kenneth Kitson, Kiattikun Chobtham, Zhigao Guo:
Effective and efficient structure learning with pruning and model averaging strategies. Int. J. Approx. Reason. 151: 292-321 (2022) - [j7]Yang Liu, Anthony C. Constantinou, Zhigao Guo:
Improving Bayesian Network Structure Learning in the Presence of Measurement Error. J. Mach. Learn. Res. 23: 324:1-324:28 (2022) - [i7]Zhigao Guo, Anthony C. Constantinou:
Parallel Sampling for Efficient High-dimensional Bayesian Network Structure Learning. CoRR abs/2202.09691 (2022) - 2021
- [j6]Ruohai Di, Peng Wang, Chuchao He, Zhigao Guo:
Constrained Adjusted Maximum a Posteriori Estimation of Bayesian Network Parameters. Entropy 23(10): 1283 (2021) - [j5]Anthony C. Constantinou, Yang Liu, Kiattikun Chobtham, Zhigao Guo, Neville Kenneth Kitson:
Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data. Int. J. Approx. Reason. 131: 151-188 (2021) - [i6]Anthony C. Constantinou, Zhigao Guo, Neville Kenneth Kitson:
Information fusion between knowledge and data in Bayesian network structure learning. CoRR abs/2102.00473 (2021) - [i5]Neville Kenneth Kitson, Anthony C. Constantinou, Zhigao Guo, Yang Liu, Kiattikun Chobtham:
A survey of Bayesian Network structure learning. CoRR abs/2109.11415 (2021) - [i4]Anthony C. Constantinou, Yang Liu, Neville Kenneth Kitson, Kiattikun Chobtham, Zhigao Guo:
Effective and efficient structure learning with pruning and model averaging strategies. CoRR abs/2112.00398 (2021) - 2020
- [j4]Zhigao Guo, Anthony C. Constantinou:
Approximate Learning of High Dimensional Bayesian Network Structures via Pruning of Candidate Parent Sets. Entropy 22(10): 1142 (2020) - [i3]Anthony C. Constantinou, Yang Liu, Kiattikun Chobtham, Zhigao Guo, Neville Kenneth Kitson:
Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data. CoRR abs/2005.09020 (2020) - [i2]Zhigao Guo, Anthony C. Constantinou:
Approximate learning of high dimensional Bayesian network structures via pruning of Candidate Parent Sets. CoRR abs/2006.04753 (2020) - [i1]Yang Liu, Anthony C. Constantinou, Zhigao Guo:
Improving Bayesian Network Structure Learning in the Presence of Measurement Error. CoRR abs/2011.09776 (2020)
2010 – 2019
- 2019
- [j3]Xiao-Guang Gao, Zhi-gao Guo, Hao Ren, Yu Yang, Da-Qing Chen, Chu-Chao He:
Learning Bayesian network parameters via minimax algorithm. Int. J. Approx. Reason. 108: 62-75 (2019) - [j2]Yu Yang, Xiao-Guang Gao, Zhi-gao Guo, Da-Qing Chen:
Learning Bayesian networks using the constrained maximum a posteriori probability method. Pattern Recognit. 91: 123-134 (2019) - 2018
- [c4]Chu-Chao He, Xiao-Guang Gao, Zhi-gao Guo:
Structure Learning of Bayesian Networks by Finding the Optimal Ordering. ICPR 2018: 177-182 - 2017
- [j1]Zhi-gao Guo, Xiao-Guang Gao, Hao Ren, Yu Yang, Ruo-hai Di, Da-Qing Chen:
Learning Bayesian network parameters from small data sets: A further constrained qualitatively maximum a posteriori method. Int. J. Approx. Reason. 91: 22-35 (2017) - [c3]Zhigao Guo, Xiaoguang Gao, Ruohai Di:
Learning Bayesian Network Parameters with Domain Knowledge and Insufficient Data. AMBN 2017: 93-104 - 2016
- [c2]Xiao-Guang Gao, Yu Yang, Zhi-gao Guo, Da-Qing Chen:
Bayesian approach to learn Bayesian networks using data and constraints. ICPR 2016: 3667-3672 - 2015
- [c1]Zhi-gao Guo, Xiao-Guang Gao, Ruo-hai Di, Yu Yang:
Learning Bayesian Network Parameters from Small Data Set: A Spatially Maximum a Posteriori Method. AMBN@JSAI-isAI 2015: 32-45
Coauthor Index
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