19 citations · 58 across the 8 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
quant-ph2023★ 19 cited
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…
eess.SY2023★ 13 cited
Quantum computing through the lens of control: A tutorial introduction
Julian Berberich, Daniel Fink
Quantum computing is a fascinating interdisciplinary research field that promises to revolutionize computing by efficiently solving previously intractable problems. Recent years ha…
quant-ph2023★ 18 cited
Robustness of quantum algorithms against coherent control errors
Julian Berberich, Daniel Fink, Christian Holm
Coherent control errors, for which ideal Hamiltonians are perturbed by unknown multiplicative noise terms, are a major obstacle for reliable quantum computing. In this paper, we pr…