Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
On the Representation and Estimation of Spatial Uncertainty
Countries citing papers authored by Peter Cheeseman
Since
Specialization
Citations
This map shows the geographic impact of Peter Cheeseman'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 Peter Cheeseman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Cheeseman more than expected).
This network shows the impact of papers produced by Peter Cheeseman. 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 Peter Cheeseman. The network helps show where Peter Cheeseman may publish in the future.
Co-authorship network of co-authors of Peter Cheeseman
This figure shows the co-authorship network connecting the top 25 collaborators of Peter Cheeseman.
A scholar is included among the top collaborators of Peter Cheeseman 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 Peter Cheeseman. Peter Cheeseman is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Samtaney, Ravi, et al.. (2000). Visualization, Extraction and Quantification of Discontinuities in Compressible Flows. NASA STI Repository (National Aeronautics and Space Administration).6 indexed citations
5.
Stolorz, Paul & Peter Cheeseman. (1998). Onboard Science Data Analysis: Opportunities, Benefits, and Effects on Mission Design. IEEE Intelligent Systems.2 indexed citations
Cheeseman, Peter & R. Wayne Oldford. (1994). Selecting Models from Data: AI and Statistics IV. Springer eBooks.16 indexed citations
11.
Cheeseman, Peter, et al.. (1994). Subpixel Resolution from Multiple Images. NASA Technical Reports Server (NASA). 241.3 indexed citations
12.
Cheeseman, Peter, Bob Kanefsky, & William M. Taylor. (1991). Where the really hard problems are. International Joint Conference on Artificial Intelligence. 331–337.591 indexed citations breakdown →
13.
Hanson, Robin, John Stutz, & Peter Cheeseman. (1991). Bayesian classification with correlation and inheritance. International Joint Conference on Artificial Intelligence. 692–698.30 indexed citations
14.
Cheeseman, Peter & Bob Kanefsky. (1990). Evolutionary tree reconstruction. NASA Technical Reports Server (NASA).2 indexed citations
15.
Smith, Randall K., Matthew W. Self, & Peter Cheeseman. (1988). A stochastic map for uncertain spatial relationships. International Symposium on Robotics. 467–474.313 indexed citations
Cheeseman, Peter. (1985). In defense of probability. International Joint Conference on Artificial Intelligence. 24(5). 1002–1009.145 indexed citations
20.
Cheeseman, Peter. (1983). A method of computing generalized Bayesian probability values for expert systems. International Joint Conference on Artificial Intelligence. 198–202.83 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.