Model Robustness Analysis
Model Robustness Analysis is a systematic methodological framework within sensitivity analysis that evaluates the stability and reliability of a model's outputs under perturbations or variations in its assumptions, parameters, or input data, thereby distinguishing it from general validation techniques by focusing specifically on the model's resilience to change.
387
Publications
23.9K
Citations
1.3K
Authors
516
Institutions
Publications per year
2017–2026
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Tsinghua University
Beijing, China
11 h-index
29 publications
1.1K citations
University of California, Berkeley
Berkeley, United States
11 h-index
16 publications
1.3K citations

Peking University
Beijing, China
8 h-index
17 publications
391 citations

Beihang University
Beijing, China
8 h-index
31 publications
1.9K citations
Stanford University
Stanford, United States
8 h-index
12 publications
576 citations
Massachusetts Institute of Technology
Cambridge, United States
8 h-index
18 publications
1.1K citations
University of California, Los Angeles
Los Angeles, United States
7 h-index
9 publications
948 citations
University of Southampton
Southampton, United Kingdom
7 h-index
11 publications
522 citations
1–8 of 516
Repository · 44 publications · 2.6K citations
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Conference · 12 publications · 1.3K citations
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7 publications · 468 citations
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