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Approximately Equivariant Quantum Neural Network for $p4m$ Group Symmetries in Images / Chang, Su Yeon (CERN ; Ecole Polytechnique, Lausanne) ; Grossi, Michele (CERN) ; Saux, Bertrand Le (European Space Agency) ; Vallecorsa, Sofia (CERN)
Quantum Neural Networks (QNNs) are suggested as one of the quantum algorithms which can be efficiently simulated with a low depth on near-term quantum hardware in the presence of noises. However, their performance highly relies on choosing the most suitable architecture of Variational Quantum Algorithms (VQAs), and the problem-agnostic models often suffer issues regarding trainability and generalization power. [...]
arXiv:2310.02323.- 2023-09-17 - 7 p. - Published in : 10.1109/QCE57702.2023.00033 Fulltext: 2310.02323 - PDF; Publication - PDF;
In : 2023 International Conference on Quantum Computing and Engineering (QCE23), Bellevue, United States, 17 - 22 Sep 2023, pp.229-235

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