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Found 2 papers, 2 papers with code
Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems
Uncertainty quantification for inverse problems in imaging has drawn much attention lately.
TransBoost: Improving the Best ImageNet Performance using Deep Transduction
This paper deals with deep transductive learning, and proposes TransBoost as a procedure for fine-tuning any deep neural model to improve its performance on any (unlabeled) test set provided at training time.
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