Robustness

Adversarial robustness refers to the ability of AI systems to withstand malicious inputs designed to deceive them.

Adversarial training is a technique used to improve the robustness of AI models against malicious inputs.

Certified Robustness ensures AI models perform reliably under various conditions by providing formal guarantees against specific failures.

Network robustness refers to the ability of a network to maintain performance despite failures or adverse conditions.

Neural network robustness refers to the ability of a neural network to maintain performance under various conditions and perturbations.