QKAN is a quantum algorithmic framework using block-encodings and QSVT to implement wide-and-shallow networks for quantum learning and compositional state preparation.
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A new ancilla-free amplitude estimation method uses statistical eigengap estimation to achieve near-optimal query-depth tradeoffs in low-depth regimes with provable guarantees.
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QKAN: quantum Kolmogorov-Arnold networks with applications in machine learning and multivariate state preparation
QKAN is a quantum algorithmic framework using block-encodings and QSVT to implement wide-and-shallow networks for quantum learning and compositional state preparation.
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Low-depth amplitude estimation via statistical eigengap estimation
A new ancilla-free amplitude estimation method uses statistical eigengap estimation to achieve near-optimal query-depth tradeoffs in low-depth regimes with provable guarantees.