OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification

no code implementations • NeurIPS 2020 • Taewon Jeong, Heeyoung Kim

The joint analysis of N sub-tasks facilitates simultaneous classification and OOD detection and, furthermore, offers an advantage, in that it does not require re-training when the number of classes for a test task differs from that for training tasks; it is sufficient to simply assume as many sub-tasks as the number of classes for the test task.

Few-Shot Learning General Classification +2