On CIFAR-10, quantization-aware training with large constant scaling factors improves noise robustness, but noisy training (injecting matching Gaussian noise during training) gives far larger robustness gains, and quantization adds little on top of it.
Walking Noise: On Layer-Specific Robustness of Neu- ral Architectures against Noisy Computations and Asso- ciated Characteristic Learning Dynamics
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On Hardening DNNs against Noisy Computations
On CIFAR-10, quantization-aware training with large constant scaling factors improves noise robustness, but noisy training (injecting matching Gaussian noise during training) gives far larger robustness gains, and quantization adds little on top of it.