3 papers
cs.CV2026
A Decision-Aware Evaluation Protocol for Uncertainty in Medical Image Segmentation
Saket Maganti, Shreyank N Gowda
Medical segmentation uncertainty is often evaluated with calibration error or pixel-level error-detection scores, but these metrics do not show whether uncertainty improves downstr…
cs.LG2026
When Graph Structure Becomes a Liability: A Critical Re-Evaluation of Graph Neural Networks for Bitcoin Fraud Detection under Temporal Distribution Shift
Saket Maganti
The consensus that GCN, GraphSAGE, GAT, and EvolveGCN outperform feature-only baselines on the Elliptic Bitcoin Dataset is widely cited but has not been rigorously stress-tested un…
cs.CV2026
Rethinking Uncertainty in Segmentation: From Estimation to Decision
Saket Maganti
In medical image segmentation, uncertainty estimates are often reported but rarely used to guide decisions. We study the missing step: how uncertainty maps are converted into actio…