Calibration Loss
Calibration Loss is a type of loss function used in machine learning that quantifies the discrepancy between predicted probabilities and empirical outcomes to ensure that the model's confidence estimates are statistically aligned with observed frequencies.
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1.1K
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61
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25
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2017–2026
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DealMVC: Dual Contrastive Calibration for Multi-view Clustering
Xihong Yang, Jiaqi Jin, Siwei Wang et al. · 2023 · 117 citations
Calibrating Deep Neural Networks using Focal Loss
Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal et al. · arXiv (Cornell University) · 2020 · 87 citations · Full text
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Rutgers, The State University of New Jersey
New Brunswick, United States
2 h-index
2 publications
98 citations

École de Technologie Supérieure
Montreal, Canada
2 h-index
5 publications
281 citations
Michigan State University
East Lansing, United States
1 h-index
3 publications
87 citations
University of Oxford
Oxford, United Kingdom
1 h-index
4 publications
348 citations
Universidad del Noreste
Tampico, Mexico
1 h-index
2 publications
494 citations
Lung Institute
Dallas, United States
1 h-index
1 publications
71 citations

University of Salerno
Fisciano, Italy
1 h-index
1 publications
71 citations
Oxford Research Group
London, United Kingdom
1 h-index
1 publications
87 citations
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Repository · 4 publications · 145 citations
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Conference · 3 publications · 122 citations
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1 publications · 81 citations
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Repository · 1 publications · 162 citations
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1 publications · 71 citations
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