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.
Efficient Geometry-aware 3D Generative Adversarial Networks
2022600 citationsEric R. Chan, Connor Z. Lin et al.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)profile →
Fusion4D
2016317 citationsMingsong Dou, Sameh Khamis et al.ACM Transactions on Graphicsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Sameh Khamis'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 Sameh Khamis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sameh Khamis more than expected).
This network shows the impact of papers produced by Sameh Khamis. 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 Sameh Khamis. The network helps show where Sameh Khamis may publish in the future.
Co-authorship network of co-authors of Sameh Khamis
This figure shows the co-authorship network connecting the top 25 collaborators of Sameh Khamis.
A scholar is included among the top collaborators of Sameh Khamis 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 Sameh Khamis. Sameh Khamis is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chan, Eric R., Connor Z. Lin, Matthew A. Chan, et al.. (2022). Efficient Geometry-aware 3D Generative Adversarial Networks. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 16102–16112.600 indexed citations breakdown →
Khamis, Sameh & Christoph H. Lampert. (2014). CoConut: Co-classification with output space regularization. British Machine Vision Conference.3 indexed citations
Khamis, Sameh, Frederick Mosteller, & David L. Wallace. (1966). Inference and Disputed Authorship: The Federalist. Revue de l Institut International de Statistique / Review of the International Statistical Institute. 34(2). 277–277.1 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.