Quantum Techniques in Machine Learning (QTML) is an annual international conference
focusing on the interdisciplinary field of quantum technology and machine learning. The goal of the conference is to gather leading academic researchers and industry players to interact through a series of scientific talks focussed on the interplay between machine learning and quantum physics.
Example topics at QTML include, but are not limited to:
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Quantum algorithms for machine learning tasks
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Quantum state reconstruction from data
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Machine learning for experimental quantum information
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Machine learning for Hamiltonian learning
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Variational quantum algorithms
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Learning and optimization with hybrid quantum-classical methods
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Quantum machine learning applications for industry
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Tensor network methods and quantum-inspired machine learning
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Data encoding and processing in quantum systems
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Quantum learning theory