Structural Limits of the Information-Theoretic Uncertainty Decomposition

arXiv:2609.39591 · cs.CV · Submitted 2026-09-30 · Read on arXiv

cs.CV

Submitted: 2026-09-30

Updated: 2026-10-08

Terminology

• Epistemic Uncertainty — 14× in this paper · explained in 9 episodes
• Entanglement — 7× in this paper · explained in 3 episodes
• Aleatoric Uncertainty — 4× in this paper · explained in 4 episodes
• Aleatoric Uncertainty (AU) — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Distribution Shift — 2× in this paper · explained in 5 episodes
• Uncertainty Decomposition — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Active Learning — 1× in this paper · explained in 6 episodes
• Additive Decomposition — 1× in this paper · explained in 1 episode
• Information-Theoretic Framework — 1× in this paper · explained in 2 episodes
• Monte Carlo dropout — 1× in this paper · explained in 2 episodes
• Out-of-Distribution (OOD) Detection — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Structural Constraints — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• Rethinking Uncertainty Quantification and Entanglement in Image Segmentation
• The Epistemic Uncertainty Hole: an issue of Bayesian Neural Networks
• Bayesian Active Learning for Classification and Preference Learning
• Decoupled Weight Decay Regularization
• Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty

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