Data Re-uploading
Data re-uploading is a circuit design pattern in quantum machine learning in which the same data is encoded into a quantum circuit multiple times, with trainable parameterized gates inserted between encodings, thereby extending the range of function frequencies the circuit can express.
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Data re-uploading is a circuit design pattern in which the same set of data is encoded into the circuit multiple times, with trainable parameterized gates inserted between each encoding.
Compared with circuits that encode data only once, data re-uploading makes the circuit's response to the input signal a higher-order Fourier series, thereby expanding the range of expressible function frequencies.
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Data re-uploading is a circuit design pattern in which the same set of data is encoded into the circuit multiple times, with trainable parameterized gates inserted between each encoding.
50%UnverifiedCompared with circuits that encode data only once, data re-uploading makes the circuit's response to the input signal a higher-order Fourier series, thereby expanding the range of expressible function frequencies.
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