Forget About Catastrophic Forgetting: Google’s Continual HyperTransformer Enables Efficient Continual Few-Shot Learning
In the new paper Continual Few-Shot Learning Using HyperTransformers, a Google Research team proposes Continual HyperTransformer, which modifies the recently published HyperTransformer few-shot learning method to sequentially update a convolutional neural network’s weights based on the information in a new task without forgetting the knowledge it learned from previous tasks.
