Papers

• Atomic-level Characterisation of Quantum Computer Arrays by Machine Learning (2019)
  Muhammad Usman et al.
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• Single-Qubit Fidelity Assessment of Quantum Annealing Hardware (2021)
  Jon Nelson et al.
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• Quantum constraint learning for quantum approximate optimization algorithm (2021)
  Santosh Kumar Radha
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• Quantum readout error mitigation via deep learning (2021)
  Jihye Kim et al.
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• Quantum circuit fidelity estimation using machine learning (2022)
  Avi Vadali et al.
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• Enhancing qubit readout with Bayesian Learning (2023)
  F. Cosco and N. Lo Gullo
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• Self-testing of semisymmetric informationally complete measurements in a qubit prepare-and-measure scenario (2023)
  G\'abor Dr\'otos et al.
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• Quantum State Tomography using Quantum Machine Learning (2023)
  Nouhaila Innan et al.
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• Quantum Algorithms for State Preparation and Data Classification based on Stabilizer Codes (2023)
  Pejman Jouzdani et al.
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• Efficient detection of nonclassicality using moments of the Wigner function (2024)
  Bivas Mallick et al.
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• Multi-stage tomography based on eigenanalysis for high-dimensional dense unitary processes in gate-based quantum computers (2024)
  Yannick Deville et al.
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