Yuling Yao

1.0k total citations
11 papers, 199 citations indexed

About

Yuling Yao is a scholar working on Statistics and Probability, Economics and Econometrics and Statistics, Probability and Uncertainty. According to data from OpenAlex, Yuling Yao has authored 11 papers receiving a total of 199 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Statistics and Probability, 2 papers in Economics and Econometrics and 2 papers in Statistics, Probability and Uncertainty. Recurrent topics in Yuling Yao's work include Statistical Methods and Bayesian Inference (2 papers), COVID-19 epidemiological studies (2 papers) and COVID-19 Pandemic Impacts (2 papers). Yuling Yao is often cited by papers focused on Statistical Methods and Bayesian Inference (2 papers), COVID-19 epidemiological studies (2 papers) and COVID-19 Pandemic Impacts (2 papers). Yuling Yao collaborates with scholars based in United States, Canada and Finland. Yuling Yao's co-authors include Andrew Gelman, Aki Vehtari, Daniel Simpson, Jonah Gabry, Måns Magnusson, Paul‐Christian Bürkner, Topi Paananen, Yu‐Sung Su, Donald Lien and Alexander van Geen and has published in prestigious journals such as Physical review. D, JAMA Network Open and International Review of Economics & Finance.

In The Last Decade

Yuling Yao

11 papers receiving 195 citations

Peers

Yuling Yao
Comparison fields: 5 of 110
  • Statistics and Probability 30
  • Artificial Intelligence 28
  • Ecology 25
  • Nature and Landscape Conservation 22
  • Experimental and Cognitive Psychology 21
Replace Steven M. LaLonde with:
Steven M. LaLonde United States
William Michael Landau United States
Topi Paananen Finland
William Jerome Wilson United States
Lauren Harrell United States
Jonathan McPherson
Rachel MacKay Altman Canada
Jennifer Pohle Germany
Cibele M. Russo Brazil
Amaury Labenne France
Steven M. LaLonde United States View profile →
Citations per field, relative to Yuling Yao
Yuling Yao · 1×
Citations per year, relative to Yuling Yao
Yuling Yao · 1×

Countries citing papers authored by Yuling Yao

Since Specialization
Citations

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

Fields of papers citing papers by Yuling Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuling Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Yuling Yao. A scholar is included among the top collaborators of Yuling Yao 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 Yuling Yao. Yuling Yao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
# Work Indexed citations
1 21
2 1
3 6
4 14
5 9
6 17
7
Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models [R package loo version 2.4.1]
53
8
Yes, but did it work?: Evaluating variational inference
2
9 48
10 24
11
Preventive maintenance timing of asphalt pavement
4

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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