Scalable Model Representation
Scalable Model Representation is a modeling framework that enables the adaptive refinement and simplification of geometric or structural detail in accordance with varying levels of resolution or resource constraints, distinguishing itself by supporting continuous and efficient transitions across levels of detail without loss of semantic integrity.
74
Publications
5.3K
Citations
315
Authors
96
Institutions
Publications per year
2017–2026
38
Parents
74
Scalable, graph-based network vulnerability analysis
Paul Ammann, Duminda Wijesekera · 2002 · 696 citations
RT-1: Robotics Transformer for Real-World Control at Scale
Anthony Brohan, Noah Brown, Justice Carbajal et al. · 2023 · 520 citations · Full text
ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation
Yufei Xu, Jing Zhang, Qiming Zhang et al. · arXiv (Cornell University) · 2022 · 351 citations · Full text
Scalable, graph-based network vulnerability analysis
Paul Ammann, Duminda Wijesekera · 2002 · 268 citations
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96

University of Surrey
Guildford, United Kingdom
3 h-index
5 publications
578 citations
University of Maryland, College Park
College Park, United States
3 h-index
9 publications
369 citations
Humboldt-Universität zu Berlin
Berlin, Germany
2 h-index
5 publications
91 citations
University of California, Davis
Davis, United States
2 h-index
4 publications
72 citations
University of Utah
Salt Lake City, United States
2 h-index
7 publications
240 citations
George Mason University
Fairfax, United States
2 h-index
6 publications
2.9K citations
Erasmus University Rotterdam
Rotterdam, The Netherlands
2 h-index
3 publications
85 citations

Queensland University of Technology
Brisbane, Australia
2 h-index
4 publications
42 citations
1–8 of 96
Repository · 7 publications · 588 citations
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Repository · 3 publications · 80 citations
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2 publications · 31 citations
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1 publications · 11 citations
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JMED · 1 publications · 30 citations
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