Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks

Hae Beom Lee, Hayeon Lee, Donghyun Na +4

While tasks could come with varying the number of instances and classes in realistic settings, the existing meta-learning approaches for few-shot classification assume that the num…