| Incremental pruning: A simple, fast, exact method for partially observable Markov decision processes AR Cassandra, ML Littman, NL Zhang arXiv preprint arXiv:1302.1525, 2013 | 696 | 2013 |
| Exploiting causal independence in Bayesian network inference NL Zhang, D Poole Journal of Artificial Intelligence Research 5, 301-328, 1996 | 655 | 1996 |
| A simple approach to Bayesian network computations NL Zhang, D Poole Proc. of the Tenth Canadian Conference on Artificial Intelligence, 1994 | 527 | 1994 |
| Hierarchical latent class models for cluster analysis NL Zhang The Journal of Machine Learning Research 5, 697-723, 2004 | 331 | 2004 |
| Algorithms for partially observable Markov decision processes W Zhang Hong Kong University of Science and Technology (Hong Kong), 2001 | 277 | 2001 |
| 贝叶斯网引论 张连文， 郭海鹏 科学出版社, 2006 | 223 | 2006 |
| Solving hidden-mode Markov decision problems SPM Choi, NL Zhang, DY Yeung, LF Lee, WC Wong, OC Au, JHP Chan, ... Journal of Comparative Economics 30 (2), 325-328, 2001 | 222* | 2001 |
| Speeding up the convergence of value iteration in partially observable Markov decision processes NL Zhang, W Zhang Journal of Artificial Intelligence Research 14, 29-51, 2001 | 200 | 2001 |
| Introduction to bayesian networks L Zhang, H Guo Beijing: Science Press, 2006 | 181* | 2006 |
| Exploiting contextual independence in probabilistic inference D Poole, NL Zhang Journal of Artificial Intelligence Research 18, 263-313, 2003 | 175 | 2003 |
| Representation, independence, and combination of evidence in the Dempster-Shafer theory L Zhang Advances in the Dempster-Shafer theory of evidence, 51-69, 1994 | 175 | 1994 |
| Model-based multidimensional clustering of categorical data T Chen, NL Zhang, T Liu, KM Poon, Y Wang Artificial Intelligence 176 (1), 2246-2269, 2012 | 148* | 2012 |
| Planning in stochastic domains: Problem characteristics and approximation NL Zhang, W Liu Technical Report HKUST-CS96-31, Department of Computer Science, Hong Kong …, 1996 | 145 | 1996 |
| Probabilistic inference in influence diagrams NL Zhang Computational intelligence 14 (4), 475-497, 1998 | 143 | 1998 |
| Latent tree models and diagnosis in traditional Chinese medicine NL Zhang, S Yuan, T Chen, Y Wang Artificial intelligence in medicine 42 (3), 229-245, 2008 | 129 | 2008 |
| A deep learning–based method for the design of microstructural materials RK Tan, NL Zhang, W Ye Structural and Multidisciplinary Optimization 61, 1417-1438, 2020 | 103 | 2020 |
| A Survey on Latent Tree Models and Applications. R Mourad, C Sinoquet, NL Zhang, T Liu, P Leray J. Artif. Intell. Res.(JAIR) 47, 157-203, 2013 | 99 | 2013 |
| A computational theory of decision networks NL Zhang, R Qi, D Poole International Journal of Approximate Reasoning 11 (2), 83-158, 1994 | 94 | 1994 |
| Hidden-mode markov decision processes for nonstationary sequential decision making SPM Choi, DY Yeung, NL Zhang Sequence learning: paradigms, algorithms, and applications, 264-287, 2001 | 87 | 2001 |
| On the role of context-specific independence in probabilistic inference NL Zhang, D Poole 16th International Joint Conference on Artificial Intelligence, IJCAI 1999 …, 1999 | 75 | 1999 |
