On MNIST, networks trained with feedback alignment resist adversarial examples generated with feedback-alignment gradients, while backprop-trained networks collapse to near-zero accuracy; the effect weakens on CIFAR-10.
Competitive learning: From interactive activation to adaptive resonance
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On the Adversarial Robustness of Neural Networks without Weight Transport
On MNIST, networks trained with feedback alignment resist adversarial examples generated with feedback-alignment gradients, while backprop-trained networks collapse to near-zero accuracy; the effect weakens on CIFAR-10.