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Found 2 papers, 1 papers with code
Enhanced countering adversarial attacks via input denoising and feature restoring
Despite the fact that deep neural networks (DNNs) have achieved prominent performance in various applications, it is well known that DNNs are vulnerable to adversarial examples/samples (AEs) with imperceptible perturbations in clean/original samples.
Defeating Catastrophic Forgetting via Enhanced Orthogonal Weights Modification
what is the upper bound of the learningable tasks sequentially for a given CL method?
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