SphUnc: Hyperspherical Uncertainty Decomposition and Causal Identification via Information Geometry

Researchers introduce SphUnc, a new AI framework that combines hyperspherical representation learning with causal modeling to improve decision-making in complex multi-agent systems. The framework decomposes uncertainty into epistemic and aleatoric components and enables better prediction calibration and interpretable causal reasoning.