Notably,we find that neuronal stochasticity plays a large role in the white box adversarial robustness, but that stochasticity alone is insufficient to explain ourresults--neuronal stochasticity interactssupralinearly with theVOneBlock features to driveadversarialrobustness.

Spiking neural networks (SNNs) are brain-inspired models that enable energy-efficient implementation on neuromorphic hardware. However, the supervised training of SNNs remains a hard problem due to the discontinuity of the spiking neuron model.

Specifically,we first propose a customized homomorphic encryption-based protocol for matrix multiplication that crucially relies on a novel compact packing technique.

The rise of Artificial Intelligence (AI) recently empowered researchers to investigate hard mathematical problems which eluded traditional approaches for decades. Y et, the use of AI in Universal Algebra (UA)--one of the fields laying the foundations of modern mathematics--is still completely unexplored.