ResQ encodes classification inputs into the Hamiltonian pulses of an analog Rydberg quantum computer and trains it as a 'residual network,' reporting accuracy gains over classical baselines that may stem from weak baseline setup.
https://www.kaggle.com/datasets/ uciml/pima-indians-diabetes-database, 2024
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ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers
ResQ encodes classification inputs into the Hamiltonian pulses of an analog Rydberg quantum computer and trains it as a 'residual network,' reporting accuracy gains over classical baselines that may stem from weak baseline setup.