Introduction to Evidential Deep Learning
– Socrates
In standard classification tasks, we have all accustomed to treating the network’s normalized probability vector as a proxy for confidence, despite its well-known limitations under uncertainty and distribution shift. In this classic setting, when the network is confident that an instance belongs to a particular class, the network assigns a high output to that class:





