Generalized Evidential Deep Learning: From a Bayesian Perspective 事件

Generalized Evidential Deep Learning: From a Bayesian Perspective arXiv:2605.25599v1 Announce Type: cross Abstract: Evidential Deep Learning (EDL) has emerged as an efficient, sampling-free strategy for uncertainty estimation. A series of EDL variants have been proposed to address specific limitations of the original framework, achieving notable success. However, the underlying theoretical structure of EDL and the relationships among these variants have received limited systematic investigation