James Q. Smith

1.0k citations
17 papers · 582 indexed · h-index 8
Topics
Bayesian Modeling and Causal Inference (7 papers)Bayesian Methods and Mixture Models (2 papers)Functional Brain Connectivity Studies (2 papers)

In The Last Decade

James Q. Smith

14 papers receiving 540 citations

Peers

James Q. Smith
Comparison fields: 5 of 92
  • Artificial Intelligence 230
  • Plant Science 227
  • Molecular Biology 197
  • Management Science and Operations Research 93
  • Statistics and Probability 52
Replace C.M. Triggs with:
C.M. Triggs New Zealand
Sophie Lèbre France
Jianhua Guo China
Wenguang Sun United States
Daniel A. Henderson United Kingdom
Daniel J. Nordman United States
Haipeng Xing United States
J. Miguel Marín Spain
Diego Colombo Italy
Xiaohai Sun Germany
James Q. Smith relative to C.M. Triggs New Zealand C.M. Triggs's profile →
Citations per field
00.5×2.8×
C.M. Triggs · 1×
Citations per year

Countries citing papers authored by James Q. Smith

Since Specialization
Citations

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

Fields of papers citing papers by James Q. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James Q. Smith. 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 James Q. Smith. The network helps show where James Q. Smith may publish in the future.

Co-authorship network of co-authors of James Q. Smith

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 0
2 6
3 11
4 22
5 2
6 22
7 3
8
Multiagent Bayesian Forecasting of Time Series with Graphical Models
0
9 255
10 0
11 2
12 12
13 44
14 160
15 40
16 2
17 1

About James Q. Smith

James Q. Smith is a scholar working on Management Science and Operations Research, Artificial Intelligence and Signal Processing, having authored 17 papers that have together received 582 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (7 papers), Bayesian Methods and Mixture Models (2 papers) and Functional Brain Connectivity Studies (2 papers). The work is most often cited by research in Management Science and Operations Research (93 citations), Artificial Intelligence (230 citations) and Statistics and Probability (52 citations). James Q. Smith has collaborated with scholars based in United Kingdom, Canada and Brazil. Frequent co-authors include Robert M. Oliver, Paul Goodwin, Andrew J. Millar, Neeraj Salathia, Paul E. Anderson, James Locke, James R. Lynn, Kieron D. Edwards, Anthony Hall and Martin Straume. Their work appears in journals such as The Plant Cell, Technometrics and Pattern Recognition.

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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