19 citations · 19 across the 3 of their papers we have counts for
4 papers · 1 filter
Multivariate quantum reservoir computing with discrete and continuous variable systems
Tobias Fellner, Jonas Merklinger, Christian Holm
Quantum reservoir computing is a promising paradigm for processing temporal data. So far, the primary focus has been on univariate time series. However, the most relevant and compl…
Robustness of quantum algorithms: Worst-case fidelity bounds and implications for design
Julian Berberich, Tobias Fellner, Robert L. Kosut +1
Errors occurring on noisy hardware pose a key challenge to reliable quantum computing. Existing techniques such as error correction, mitigation, or suppression typically separate t…
The interplay of robustness and generalization in quantum machine learning
Julian Berberich, Tobias Fellner, Christian Holm
While adversarial robustness and generalization have individually received substantial attention in the recent literature on quantum machine learning, their interplay is much less…
Training robust and generalizable quantum models
Julian Berberich, Daniel Fink, Daniel Pranjić +2
Adversarial robustness and generalization are both crucial properties of reliable machine learning models. In this paper, we study these properties in the context of quantum machin…