SLL Small

Reported on 2 benchmarks across 1 task · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Adversarial2 results

Adversarial DefenseonCIFAR-100
Accuracy· 2023-03-06
40.7
best: 42.7 (SLL X-Large)
A Unified Algebraic Perspective on Lipschitz Neural Networks arXiv:2303.03169
Adversarial DefenseonCIFAR-10
Accuracy· 2023-03-06
68.1
best: 90.03 (WRN-28-10)
A Unified Algebraic Perspective on Lipschitz Neural Networks arXiv:2303.03169