Uncertainty Estimation using Variance-Gated Distributions 事件

Uncertainty Estimation using Variance-Gated Distributions arXiv:2509.08846v2 Announce Type: replace-cross Abstract: Evaluation of per-sample uncertainty quantification from neural networks is essential for decision-making involving high-risk applications. A common approach is to use the predictive distribution from Bayesian or approximation models and decompose the corresponding predictive uncertainty into epistemic (model-related) and aleatoric (data-related) components. However, additive deco