14 citations · 32 across the 14 of their papers we have counts for
3 papers · 1 filter
Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning
Maximilian Wendlinger, Kilian Tscharke, Pascal Debus
One of the key obstacles in traditional deep learning is the reduction in model transparency caused by increasingly intricate model functions, which can lead to problems such as ov…
Efficient Quantum One-Class Support Vector Machines for Anomaly Detection Using Randomized Measurements and Variable Subsampling
Michael Kölle, Afrae Ahouzi, Pascal Debus +4
Quantum one-class support vector machines leverage the advantage of quantum kernel methods for semi-supervised anomaly detection. However, their quadratic time complexity with resp…
A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models
Maximilian Wendlinger, Kilian Tscharke, Pascal Debus
Quantum machine learning (QML) continues to be an area of tremendous interest from research and industry. While QML models have been shown to be vulnerable to adversarial attacks m…