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  1. Quantum machine learning

    Quantum machine learning is an emerging interdisciplinary research area at the intersection of quantum physics and machine learning. The most common use

  2. Machine learning

    for machine learning research Predictive analytics Quantum machine learning Machine-learning applications in bioinformatics Seq2seq Fairness (machine learning)

  3. Outline of machine learning

    Cross-disciplinary fields involving machine learning Adversarial machine learning Predictive analytics Quantum machine learning Robot learning Developmental robotics

  4. Machine learning in physics

    Applying classical methods of machine learning to the study of quantum systems (sometimes called quantum machine learning) is the focus of an emergent

  5. List of datasets for machine-learning research

    for machine-learning research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major

  6. Quantum computing

    Post-quantum cryptography Quantum annealing Quantum bus Quantum cognition Quantum cryptography Quantum logic gate Quantum machine learning Quantum threshold

  7. Cambridge Quantum Computing

    has built enterprise applications for quantum chemistry, quantum machine learning, quantum cryptography and quantum finance. CQC was selected as one of

  8. Quantum neural network

    (which are widely used in machine learning for the important task of pattern classification) with the advantages of quantum information in order to develop

  9. Restricted Boltzmann machine

    classification,collaborative filtering, feature learning,topic modelling and even many body quantum mechanics. They can be trained in either supervised

  10. Quantum entanglement

    Quantum entanglement is the physical phenomenon that occurs when a pair or group of particles is generated, interact, or share spatial proximity in a