Investigating the Effect of Noise on the Training Performance of Hybrid Quantum Neural Networks

Documenti analoghi

• Cutting is All You Need: Execution of Large-Scale Quantum Neural Networks on Limited-Qubit Devices
  di: Marchisio, Alberto, et al.
  Pubblicazione: (2024)
• HQNET: Harnessing Quantum Noise for Effective Training of Quantum Neural Networks in NISQ Era
  di: Kashif, Muhammad, et al.
  Pubblicazione: (2024)
• NRQNN: The Role of Observable Selection in Noise-Resilient Quantum Neural Networks
  di: Kashif, Muhammad, et al.
  Pubblicazione: (2025)
• Rethinking Expressibility-Trainability Trade-off in Hybrid Quantum Neural Networks
  di: Kashif, Muhammad, et al.
  Pubblicazione: (2026)
• Noisy HQNNs: A Comprehensive Analysis of Noise Robustness in Hybrid Quantum Neural Networks
  di: Ahmed, Tasnim, et al.
  Pubblicazione: (2025)