747 citations · 1.2k across the 24 of their papers we have counts for
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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…
Classical Verification of Quantum Learning
Matthias C. Caro, Marcel Hinsche, Marios Ioannou +2
Quantum data access and quantum processing can make certain classically intractable learning tasks feasible. However, quantum capabilities will only be available to a select few in…
On the average-case complexity of learning output distributions of quantum circuits
Alexander Nietner, Marios Ioannou, Ryan Sweke +4
In this work, we show that learning the output distributions of brickwork random quantum circuits is average-case hard in the statistical query model. This learning model is widely…