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Showing 1 to 5 of 5 for “"Quantum Machine Learning (QML)"”.

  1. Quantum Machine Learning Applied to Astronomical Datasets

    This dissertation investigates the application of quantum machine learning techniques in the field of astronomy. The focus is on a variety of supervised and unsupervised tasks, including classification, clustering, and anomaly detection. Quantum kernel methods, such as quantum-enhanced support …

    stellenbosch Repository record for Quantum Machine Learning Applied to Astronomical Datasets (opens in a new tab)

  2. Spatial Quantum Computation in Graph Optimization Problems in Transportation Applications

    … of life. This research explores the potential of Quantum Computing (QC) to address spatial optimization problems in transportation systems. By leveraging the principles of quantum mechanics, this research aims to enhance the efficiency and effectiveness of transportation networks through QC-based …

    york Repository record for Spatial Quantum Computation in Graph Optimization Problems in Transportation Applications (opens in a new tab)

  3. Towards Real-World Quantum Machine Learning

    Quantum machine learning (QML) promises new representational and computational capabilities, yet practical deployment on near-term hardware is hampered by resource overheads, depth constraints, and fragile trainability. This thesis advances resource-aware QML by proposing architectures and kernels …

    ottawa-retro Repository record for Towards Real-World Quantum Machine Learning (opens in a new tab)

  4. Enhancing Software Defect Prediction: Investigating Diverse Representations of Source Code as Feature Values in Classical and Quantum Machine Learning Approaches

    … challenges because using some feature values in Machine/ Deep Learning (ML/ DL) models might seem infeasible and impractical. For instance, predicting whether a software component is buggy or non-buggy based on a feature like the ``age of the component" provides limited actionable insight for …

    sask Repository record for Enhancing Software Defect Prediction: Investigating Diverse Representations of Source Code as Feature Values in Classical and Quantum Machine Learning Approaches (opens in a new tab)

  5. Fundamentals of Quantum Communication Networks: Scalability, Efficiency, and Distributed Quantum Machine Learning

    The future quantum Internet (QI) will transform today's communication networks and user experiences by providing unparalleled security levels, superior quantum computational powers, along with enhanced sensing accuracy and data processing capabilities. These features will be enabled through …

    vt Repository record for Fundamentals of Quantum Communication Networks: Scalability, Efficiency, and Distributed Quantum Machine Learning (opens in a new tab)