Papers

• Dendritic In-Context Learning in a Single-Layer Spiking Neural Network (2026)
  Juwei Shen et al.
  3.45
• Graph-Based Bayesian Optimization for Quantum Circuit Architecture Search with Uncertainty Calibrated Surrogates (2025)
  Prashant Kumar Choudhary et al.
  2.62
• Superposed parameterised quantum circuits (2025)
  Viktoria Patapovich et al.
  1.22
• DeQompile: quantum circuit decompilation using genetic programming for explainable quantum architecture search (2025)
  Shubing Xie et al.
  1.11
• Introduction to Quantum Machine Learning and Quantum Architecture Search (2025)
  Samuel Yen-Chi Chen et al.
  1.11
• Method for noise-induced regularization in quantum neural networks (2024)
  Viacheslav Kuzmin et al.
  0.89
• Multi-objective design of quantum circuits using genetic programming (2016)
  Moein Sarvaghad-Moghaddam
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• Quantum autoencoders via quantum adders with genetic algorithms (2017)
  L. Lamata et al.
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• Evaluation of Parameterized Quantum Circuits: on the relation between classification accuracy, expressibility and entangling capability (2020)
  Thomas Hubregtsen et al.
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• Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional Regression (2022)
  Jun Qi et al.
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• GASP -- A Genetic Algorithm for State Preparation (2023)
  Floyd M. Creevey et al.
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• T-Count Optimizing Genetic Algorithm for Quantum State Preparation (2024)
  Andrew Wright et al.
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• Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacity (2024)
  Samuel Yen-Chi Chen
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• Quantum Time-Series Learning with Evolutionary Algorithms (2024)
  Vignesh Anantharamakrishnan and M\'arcio M. Taddei
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• Quantum memristors for neuromorphic quantum machine learning (2024)
  Lucas Lamata
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