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About Efficient Learning For Deep Quantum Neural Networks
1) The document proposes a method for efficiently training deep quantum neural networks (QNNs) using quantum neurons as building blocks. 2) The training is done using fidelity as a cost function and can be implemented classically or efficiently on a quantum computer. 3) The method allows for fast optimization of deep QNNs while requiring fewer qubits that scale only with the network width, not depth.
Detailed Information
Author: | ['ivi'] |
---|---|
Publication Year: | 2019 |
Pages: | 24 |
Language: | English |
Format: | |
Price: | FREE |
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