509 citations · 3.2k across the 61 of their papers we have counts for
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quant-ph2021★ 64 cited
Importance of Kernel Bandwidth in Quantum Machine Learning
Ruslan Shaydulin, Stefan M. Wild
Quantum kernel methods are considered a promising avenue for applying quantum computers to machine learning problems. Identifying hyperparameters controlling the inductive bias of…
quant-ph2021★ 40 cited
Exploiting Symmetry Reduces the Cost of Training QAOA
Ruslan Shaydulin, Stefan M. Wild
A promising approach to the practical application of the Quantum Approximate Optimization Algorithm (QAOA) is finding QAOA parameters classically in simulation and sampling the sol…