PAH learns per-task classifier heads from compact learned prototypes via a hypernetwork and uses dual knowledge distillation to keep accuracy high and forgetting near zero on Split-CIFAR100 and TinyImageNet.
Resurrecting old classes with new data for exemplar-free con- tinual learning
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Prototype Augmented Hypernetworks for Continual Learning
PAH learns per-task classifier heads from compact learned prototypes via a hypernetwork and uses dual knowledge distillation to keep accuracy high and forgetting near zero on Split-CIFAR100 and TinyImageNet.