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Beyond Homoscedasticity: Decoupled Uncertainty Optimization for Deep Imbalanced Regression
Deep Imbalanced Regression (DIR) is pervasive in continuous prediction tasks across diverse modalities, such as age estimation, depth prediction, and protein mutation activity prediction, where label-scarce tail samples often carry higher practical value. However, most existing methods still learn d
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