Benchmarking adversarially robust quantum machine learning at scale
Machine learning (ML) methods such as artificial neural networks are rapidly becoming ubiquitous in modern science, technology, and industry.Despite their accuracy and sophistication, neural networks can be easily fooled by carefully designed malicious inputs known as adversarial attacks.While such vulnerabilities remain a serious challenge for cla