arXiv stat.ML
· Papers
Uncertainty quantification for trustworthy deep learning: Methods and measures
arXiv:2607.28248v1 Announce Type: new Abstract: The deployment of deep neural networks in safety-critical domains demands reliable estimates of predictive confidence, yet conventional architectures lack principled uncertainty quantification. This survey provides a structured, critical review of methods for Uncertainty