24 citations · 24 across the 4 of their papers we have counts for
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quant-ph2026
Adaptive Relational Learning on Multi-instance Quantum Data with Photonic Processors
Marcin Jastrzebski, Shang Yu, Raj B. Patel +1
Loading multiple quantum states in parallel into a quantum machine learning (QML) model can unlock learning tasks where key information resides in the \emph{relations} between stat…
quant-ph2026
Learning structural balance of graphs from quantum spectral features
Stefano Scali, Oleksandr Kyriienko
We develop a quantum approach to spectral feature extraction from the density of states (DOS) of a problem-dependent Hamiltonian, and apply it to machine learning on signed graphs.…
quant-ph2022★ 24 cited
Unsupervised quantum machine learning for fraud detection
Oleksandr Kyriienko, Einar B. Magnusson
We develop quantum protocols for anomaly detection and apply them to the task of credit card fraud detection (FD). First, we establish classical benchmarks based on supervised and…