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Published in 2021 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.1c00294
Abstract: Quantum machine learning algorithms, the extensions of machine learning to quantum regimes, are believed to be more powerful as they leverage the power of quantum properties. Quantum machine learning methods have been employed to solve…
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Keywords:
machine;
quantum machine;
electronic structure;
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Published in 2018 at "Nature Communications"
DOI: 10.1038/s41467-018-06598-z
Abstract: Considering recent advancements and successes in the development of efficient quantum algorithms for electronic structure calculations—alongside impressive results using machine learning techniques for computation—hybridizing quantum computing with machine learning for the intent of performing electronic…
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machine;
quantum machine;
machine learning;
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Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-68911-5
Abstract: We implement an all-optical setup demonstrating kernel-based quantum machine learning for two-dimensional classification problems. In this hybrid approach, kernel evaluations are outsourced to projective measurements on suitably designed quantum states encoding the training data, while…
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machine learning;
quantum machine;
space;
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Published in 2021 at "Chemical Science"
DOI: 10.1039/d1sc01185e
Abstract: The computation of tautomer ratios of druglike molecules is enormously important in computer-aided drug discovery, as over a quarter of all approved drugs can populate multiple tautomeric species in solution. Unfortunately, accurate calculations of aqueous…
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Keywords:
tautomer ratios;
quantum machine;
machine learning;
quantum chemical ... See more keywords
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Published in 2017 at "Physical review letters"
DOI: 10.1103/physrevlett.118.080501
Abstract: Machine learning is a fascinating and exciting field within computer science. Recently, this excitement has been transferred to the quantum information realm. Currently, all proposals for the quantum version of machine learning utilize the finite-dimensional…
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Keywords:
machine;
quantum machine;
machine learning;
learning infinite ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3195044
Abstract: Quantum technologies have become powerful tools for a wide range of application disciplines, which tend to range from chemistry to agriculture, natural language processing, and healthcare due to exponentially growing computational power and advancement in…
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machine;
machine learning;
applications biomedical;
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Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3255417
Abstract: Prognostics and Health Management (PHM) concerns predicting machines’ behavior to support maintenance decisions through failure modes diagnosis and prognosis. Diagnosis is broadly applied in the context of rotating machines’ state classification using several traditional Machine…
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Published in 2023 at "IEEE Wireless Communications"
DOI: 10.1109/mwc.003.2200382
Abstract: Immersive and mission-critical data-driven applications, such as virtual or augmented reality, tactile Internet, industrial automation, and autonomous mobility, are creating unprecedented challenges for ultra-reliable and low-latency communication (URLLC) in the sixth generation (6G) networks. Machine…
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machine;
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machine intelligence;
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Published in 2023 at "Atmosphere"
DOI: 10.3390/atmos14060944
Abstract: Despite the growing impact of emissions on our health and the environment, there remains an unmet need for emission concentration prediction and forecasting. The accumulating monitoring station and satellite data make the problem well-suited for…
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Keywords:
quantum machine;
machine learning;
emission;
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Published in 2022 at "Entropy"
DOI: 10.3390/e24111656
Abstract: Quantum Machine Learning (QML) has not yet demonstrated extensively and clearly its advantages compared to the classical machine learning approach. So far, there are only specific cases where some quantum-inspired techniques have achieved small incremental…
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Keywords:
algorithms;
quantum;
finance;
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Published in 2023 at "Entropy"
DOI: 10.3390/e25020287
Abstract: Despite its undeniable success, classical machine learning remains a resource-intensive process. Practical computational efforts for training state-of-the-art models can now only be handled by high speed computer hardware. As this trend is expected to continue,…
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Keywords:
machine;
quantum machine;
machine learning;
learning review ... See more keywords