This paper demonstrates a quantum Gaussian process using HHL and approximate quantum compiling on IBM hardware for a 32x32 kernel, but the estimated line resistance and inductance deviate substantially from true values and the objective rescaling is not mathematically justified.
That is, perform the transformation |0⟩nb 7→ |b⟩nb
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Quantum multi-output Gaussian Processes based Machine Learning for Line Parameter Estimation in Electrical Grids
This paper demonstrates a quantum Gaussian process using HHL and approximate quantum compiling on IBM hardware for a 32x32 kernel, but the estimated line resistance and inductance deviate substantially from true values and the objective rescaling is not mathematically justified.