212 citations · 712 across the 23 of their papers we have counts for
5 papers · 1 filter
Variational measurement-based quantum computation for generative modeling
Arunava Majumder, Marius Krumm, Tina Radkohl +4
Measurement-based quantum computation (MBQC) offers a fundamentally unique paradigm to design quantum algorithms. Indeed, due to the inherent randomness of quantum measurements, th…
Potential and limitations of random Fourier features for dequantizing quantum machine learning
Ryan Sweke, Erik Recio-Armengol, Sofiene Jerbi +4
Quantum machine learning is arguably one of the most explored applications of near-term quantum devices. Much focus has been put on notions of variational quantum machine learning…
Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning
Francesco Preti, Michael Schilling, Sofiene Jerbi +4
Shortening quantum circuits is crucial to reducing the destructive effect of environmental decoherence and enabling useful algorithms. Here, we demonstrate an improvement in such c…
Shadows of quantum machine learning
Sofiene Jerbi, Casper Gyurik, Simon C. Marshall +2
Quantum machine learning is often highlighted as one of the most promising practical applications for which quantum computers could provide a computational advantage. However, a ma…
The power and limitations of learning quantum dynamics incoherently
Sofiene Jerbi, Joe Gibbs, Manuel S. Rudolph +4
Quantum process learning is emerging as an important tool to study quantum systems. While studied extensively in coherent frameworks, where the target and model system can share qu…