Changhe Yuan

1.1k total citations
46 papers, 508 citations indexed

About

Changhe Yuan is a scholar working on Artificial Intelligence, Management Science and Operations Research and Signal Processing. According to data from OpenAlex, Changhe Yuan has authored 46 papers receiving a total of 508 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 17 papers in Management Science and Operations Research and 8 papers in Signal Processing. Recurrent topics in Changhe Yuan's work include Bayesian Modeling and Causal Inference (32 papers), Data Quality and Management (14 papers) and Data Management and Algorithms (8 papers). Changhe Yuan is often cited by papers focused on Bayesian Modeling and Causal Inference (32 papers), Data Quality and Management (14 papers) and Data Management and Algorithms (8 papers). Changhe Yuan collaborates with scholars based in United States, Finland and China. Changhe Yuan's co-authors include Brandon Malone, Marek J. Drużdżel, Tsai-Ching Lu, Eric A. Hansen, Patrick R. Hof, Tingting Wu, Jin Fan, Qiong Wu, Xingchao Wang and Zhixian Gao and has published in prestigious journals such as NeuroImage, Cerebral Cortex and BMC Bioinformatics.

In The Last Decade

Changhe Yuan

42 papers receiving 487 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Changhe Yuan United States	12	274	97	97	56	41	46	508
Serdar Kadıoğlu United States	8	120 0.4×	46 0.5×	27 0.3×	48 0.9×	44 1.1×	27	298
S.D. Katebi Iran	13	303 1.1×	161 1.7×	25 0.3×	58 1.0×	49 1.2×	31	629
Adriana Albu Romania	10	155 0.6×	41 0.4×	30 0.3×	42 0.8×	14 0.3×	47	454
Marek Grześ United Kingdom	12	324 1.2×	58 0.6×	45 0.5×	49 0.9×	10 0.2×	34	469
Mohammad Shafiul Alam Bangladesh	12	197 0.7×	26 0.3×	50 0.5×	30 0.5×	20 0.5×	44	421
Yihong Dong China	12	225 0.8×	55 0.6×	18 0.2×	116 2.1×	32 0.8×	52	500
Tsung-Yu Hsieh Taiwan	10	174 0.6×	122 1.3×	20 0.2×	31 0.6×	44 1.1×	25	400
Jiong Zhu China	7	206 0.8×	33 0.3×	25 0.3×	72 1.3×	16 0.4×	30	434
Leonard A. Breslow United States	9	249 0.9×	42 0.4×	18 0.2×	53 0.9×	26 0.6×	19	556
Gauthier Doquire Belgium	10	276 1.0×	162 1.7×	16 0.2×	170 3.0×	36 0.9×	16	610

Countries citing papers authored by Changhe Yuan

Since Specialization

Citations

This map shows the geographic impact of Changhe Yuan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Changhe Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Changhe Yuan more than expected).

Fields of papers citing papers by Changhe Yuan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Changhe Yuan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Changhe Yuan. The network helps show where Changhe Yuan may publish in the future.

Co-authorship network of co-authors of Changhe Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Changhe Yuan. A scholar is included among the top collaborators of Changhe Yuan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Changhe Yuan. Changhe Yuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Yuan, Changhe, et al.. (2020). Does Applying Deep Learning in Financial Sentiment Analysis Lead to Better Classification Performance. Economics bulletin. 40(2). 1091–1105. 6 indexed citations

Yang, Jiaqi, et al.. (2020). Solving Multiple Inference by Minimizing Expected Loss.. 65–76.

Ji, Geng, Huazhong Ning, Changhe Yuan, et al.. (2019). Variational Training for Large-Scale Noisy-OR Bayesian Networks.. Uncertainty in Artificial Intelligence. 873–882. 1 indexed citations

Chen, Cong, Changhe Yuan, Ze Ye, & Chao Chen. (2018). Solving M-Modes in Loopy Graphs Using Tree Decompositions. 145–156. 2 indexed citations

Yuan, Changhe, et al.. (2016). Solving M-modes using heuristic search. International Joint Conference on Artificial Intelligence. 3584–3590. 4 indexed citations

Malone, Brandon, et al.. (2014). Finding optimal Bayesian network structures with constraints learned from data. Uncertainty in Artificial Intelligence. 200–209. 24 indexed citations

Yuan, Changhe, et al.. (2012). Machine Learning Analysis of the Relationship Between Changes in Immunological Parameters and Changes in Resistance to Listeria monocytogenes: A New Approach for Risk Assessment and Systems Immunology. Toxicological Sciences. 129(1). 57–73. 3 indexed citations

Yuan, Changhe, et al.. (2012). Mixture model analysis reflecting dynamics of the population diversity of 2009 pandemic H1N1 influenza virus. In Silico Biology. 11(5-6). 225–236. 1 indexed citations

Malone, Brandon, Changhe Yuan, Eric A. Hansen, & Susan M. Bridges. (2011). Improving the scalability of optimal Bayesian network learning with external-memory frontier breadth-first branch and bound search. Uncertainty in Artificial Intelligence. 479–488. 17 indexed citations

10.

Yuan, Changhe, et al.. (2011). Most Relevant Explanation: computational complexity and approximation methods. Annals of Mathematics and Artificial Intelligence. 61(3). 159–183. 8 indexed citations

11.

Yuan, Changhe. (2009). Some properties of most relevant explanation. 106(1). 118–126. 3 indexed citations

12.

Yuan, Changhe & Eric A. Hansen. (2009). Efficient computation of jointree bounds for systematic MAP search. International Joint Conference on Artificial Intelligence. 1982–1989. 14 indexed citations

13.

Yuan, Changhe & Tsai-Ching Lu. (2008). A general framework for generating multivariate explanations in Bayesian networks. National Conference on Artificial Intelligence. 1119–1124. 6 indexed citations

14.

Yuan, Changhe & Marek J. Drużdżel. (2007). Importance Sampling for General Hybrid Bayesian Networks. International Conference on Artificial Intelligence and Statistics. 652–659. 7 indexed citations

15.

Yuan, Changhe & Marek J. Drużdżel. (2007). Generalized evidence pre-propagated importance sampling for hybrid Bayesian networks. National Conference on Artificial Intelligence. 1296–1302. 3 indexed citations

16.

Sun, Xiaoxun, Marek J. Drużdżel, & Changhe Yuan. (2006). Dynamic Weighting A* Search-based MAP Algorithm for Bayesian Networks.. International Joint Conference on Artificial Intelligence. 2385–2390. 11 indexed citations

17.

Yuan, Changhe & Marek J. Drużdżel. (2006). Hybrid Loopy Belief Propagation.. 317–324. 8 indexed citations

18.

Drużdżel, Marek J. & Changhe Yuan. (2006). Importance sampling for bayesian networks: principles, algorithms, and performance. 1 indexed citations

19.

Yuan, Changhe & Marek J. Drużdżel. (2005). How Heavy Should the Tails Be. The Florida AI Research Society. 799–805. 5 indexed citations

20.

Yuan, Changhe, Tsai-Ching Lu, & Marek J. Drużdżel. (2004). Annealed MAP. Uncertainty in Artificial Intelligence. 628–635. 26 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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