Springer Science and Business Media LLC
ESCI-ISI SCOPUS (2019-2023)
2524-4906
2524-4914
Cơ quản chủ quản: Springer Nature , Springer Science and Business Media Deutschland GmbH
Lĩnh vực:
Artificial IntelligenceTheoretical Computer ScienceSoftwareApplied MathematicsComputational Theory and Mathematics
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Layerwise learning for quantum neural networksAbstract With the increased focus on quantum circuit learning for near-term applications on quantum devices, in conjunction with unique challenges presented by cost function landscapes of parametrized quantum circuits, strategies for effective training are becoming increasingly important. In order to ameliorate some of these challenges, we investigate a layerwise le... ...
Tập 3 Số 1 - 2021
Evaluation of parameterized quantum circuits: on the relation between classification accuracy, expressibility, and entangling capabilityAbstract An active area of investigation in the search for quantum advantage is quantum machine learning. Quantum machine learning, and parameterized quantum circuits in a hybrid quantum-classical setup in particular, could bring advancements in accuracy by utilizing the high dimensionality of the Hilbert space as feature space. But is the ability of a quantum circu... ...
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Decoding surface code with a distributed neural network–based decoderAbstract There has been a rise in decoding quantum error correction codes with neural network–based decoders, due to the good decoding performance achieved and adaptability to any noise model. However, the main challenge is scalability to larger code distances due to an exponential increase of the error syndrome space. Note that successfully decoding the surface cod... ...
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A continuous-variable quantum-inspired algorithm for classical image segmentation
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K-spin Hamiltonian for quantum-resolvable Markov decision processes
Tập 2 - Trang 1-11 - 2020
The Markov decision process is the mathematical formalization underlying the modern field of reinforcement learning when transition and reward functions are unknown. We derive a pseudo-Boolean cost function that is equivalent to a K-spin Hamiltonian representation of the discrete, finite, discounted Markov decision process with infinite horizon. This K-spin Hamiltonian furnishes a starting point f......
Binary classification with classical instances and quantum labelsAbstract In classical statistical learning theory, one of the most well-studied problems is that of binary classification. The information-theoretic sample complexity of this task is tightly characterized by the Vapnik-Chervonenkis (VC) dimension. A quantum analog of this task, with training data given as a quantum state has also been intensely studied and is now kn... ...
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