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Continual Learning with Dependency Preserving Hypernetworks
However, the continual learning performance of existing hypernetwork based approaches are affected by the assumption of independence of the weights across the layers in order to maintain parameter efficiency.
CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks
Our approach is based on learning a set of global and task-specific parameters.
AdvGAN++ : Harnessing latent layers for adversary generation
Adversarial examples are fabricated examples, indistinguishable from the original image that mislead neural networks and drastically lower their performance.
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