Artificial Intelligence #deep learning#reinforcement learning
New Visualization Framework Reveals Spatial Sources of Uncertainty in Deep Learning Models
Researchers propose a novel framework called Uncertainty Activation Map (UAM) that visualizes two types of uncertainty – vacuity (lack of evidence) and dissonance (conflicting evidence) – at pixel level. Combining Evidential Deep Learning (EDL) with Full-Gradient Class Activation Mapping (FullGrad), UAM provides theoretically grounded spatial maps to help identify when and why deep neural networks are uncertain, a critical capability for deploying reliable AI in safety-critical domains.
Jun 16, 2026 2 sources