When uncertainty quantification fails: structural vulnerabilities and corrections for selective prediction under clinical class imbalance

arXiv:2610.37561 · cs.LG, cs.AI · Submitted 2026-10-27 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-10-27

Updated: 2026-10-27

Terminology

• Class Imbalance — 1× in this paper · explained in 3 episodes
• Selective Prediction — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 9 episodes

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks