86 citations · 408 across the 11 of their papers we have counts for
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Representation Learning via Quantum Neural Tangent Kernels
Junyu Liu, Francesco Tacchino, Jennifer R. Glick +2
Variational quantum circuits are used in quantum machine learning and variational quantum simulation tasks. Designing good variational circuits or predicting how well they perform…
Approximate Solutions of Combinatorial Problems via Quantum Relaxations
Bryce Fuller, Charles Hadfield, Jennifer R. Glick +8
Combinatorial problems are formulated to find optimal designs within a fixed set of constraints. They are commonly found across diverse engineering and scientific domains. Understa…
Covariant quantum kernels for data with group structure
Jennifer R. Glick, Tanvi P. Gujarati, Antonio D. Corcoles +4
The use of kernel functions is a common technique to extract important features from data sets. A quantum computer can be used to estimate kernel entries as transition amplitudes o…
Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
Sau Lan Wu, Shaojun Sun, Wen Guan +20
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In…