Ya Xue

3.6k citations
29 papers · 2.6k indexed · 1 hit paper · h-index 13

Ya Xue

27 papers receiving 2.5k citations

Hit Papers

Bayesian Compressive Sensing1.8k200820262014202050010001.5k

Peers

Ya Xue
Comparison fields: 5 of 120
  • Computational Mechanics 1.2k
  • Signal Processing 614
  • Acoustics and Ultrasonics 28
  • Computer Vision and Pattern Recognition 493
  • Artificial Intelligence 675
Replace Shihao Ji with:
Shihao Ji United States
Yuantao Gu China
Dimitry Gorinevsky United States
Xiaoming Huo United States
Petros T. Boufounos United States
B. K. Natarajan United States
Namrata Vaswani United States
Kwangmoo Koh United States
Martin J. Strauss United States
Gongguo Tang United States
Ya Xue relative to Shihao Ji United States Shihao Ji's profile →
Citations per field
00.5×
Shihao Ji · 1×
Citations per year

Countries citing papers authored by Ya Xue

Since Specialization
Citations

This map shows the geographic impact of Ya Xue'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 Ya Xue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ya Xue more than expected).

Fields of papers citing papers by Ya Xue

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ya Xue. 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 Ya Xue. The network helps show where Ya Xue may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Ya Xue, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ya Xue Line = papers co-authored together Ya Xue links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20258
2 20231
3 202213
4 20223
5 201735
6 201711
7
Potential Benefit,Risk Preference and Farmers' Willingness to Plant Genetically Modified Crops:Based on a Survey of over 700 Households from five Provinces in China
20141
8 201231
9 20086
10
Bayesian Compressive Sensingbreakdown →
20081763
11 200845
12 200776
13 20074
14 200718
15 2005121
16 200316
17 20039
18 20022
19 20011
20
DETERMINATION OF KAISER POINT IN MEASUREMENT OF GEO-STRESS WITH ACOUSTIC EMISSION
20000

About Ya Xue

Ya Xue is a scholar working on Statistics and Probability, Instrumentation and Artificial Intelligence, having authored 29 papers that have together received 2.6k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (6 papers), Face and Expression Recognition (3 papers), Target Tracking and Data Fusion in Sensor Networks (3 papers), Statistical Methods and Bayesian Inference (3 papers), Sparse and Compressive Sensing Techniques (2 papers), Machine Learning and Algorithms (2 papers), Fault Detection and Control Systems (2 papers) and Synthesis and properties of polymers (2 papers). The work is most often cited by research in Computational Mechanics (1.2k citations), Signal Processing (614 citations) and Acoustics and Ultrasonics (28 citations). Ya Xue has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Lawrence Carin, Shihao Ji, Xuejun Liao, Balaji Krishnapuram, David B. Dunson, D. A. Williams, Darryl Morrell, Weizhong Yan, David P. Williams and Lindsey Smith Taillie. Their work appears in journals such as Journal of Applied Polymer Science, Polymer Degradation and Stability, Frontiers in Psychology, Neural Networks and Journal of the American Statistical Association.

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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