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BayesAdapter: Enhanced Uncertainty Estimation in CLIP Few-Shot Adaptation
Pablo Morales-Álvarez
, Stergios Christodoulidis
, Maria Vakalopoulou
, Pablo Piantanida
,
Jose Dolz
École de technologie supérieure
Software and Information Technology Engineering Department
LIVIA - Imaging, Vision and Artificial Intelligence Laboratory
University of Granada
Université Paris-Saclay
École de technologie supérieure
Université de Montréal
Research output
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Contribution to journal
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Journal Article
›
peer-review
1
Citation (Scopus)
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Keyphrases
Uncertainty Estimation
100%
Adapter
100%
Few-shot Adaptation
100%
Discriminative Performance
50%
Publicly Available
25%
Popular
25%
Parameter Space
25%
Machine Learning
25%
Learning Methods
25%
Transfer Learning
25%
Probability Distribution
25%
Bayesian Inference
25%
Large Animal Model
25%
Recognition Task
25%
Visual Recognition
25%
Backpropagation
25%
Learnability
25%
Downstream Task
25%
Single Point
25%
Probabilistic Framework
25%
Prompt Learning
25%
Zero-shot Learning
25%
Quality Uncertainty
25%
MAP Inference
25%
Selective Classification
25%
Safe Deployment
25%
Vision-Language Models
25%
Pre-trained Vision-Language Models
25%
Parameter-efficient
25%
Zero Transfer
25%
Computer Science
Language Modeling
100%
Uncertainty Estimation
100%
Machine Learning
50%
Learning System
50%
Transfer Learning
50%
Paradigm Shift
50%
Parameter Space
50%
Probabilistic Framework
50%
Prompt Learning
50%
Zero-Shot Learning
50%
Supplementary Material
50%
Probability
50%