Enhancing Generalization of Universal Adversarial Perturbation through Gradient Aggregation vs RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks

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Enhancing Generalization of Universal Adversarial Perturbation through Gradient Aggregation
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Enhancing Generalization of Universal Adversarial Perturbation through Gradient Aggregation

Deep neural networks are vulnerable to universal adversarial perturbation (UAP), an instance-agnostic perturbation capable of fooling the target model for most samples.

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RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks
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RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks

Spiking Neural Networks (SNNs) as one of the biology-inspired models have received much attention recently.

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