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ESCI-ISI SCOPUS (2019-2025)
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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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Các bài báo tiêu biểu
Layerwise learning for quantum neural networks
Tập 3 Số 1 - 2021
AbstractWith 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 learning strategy for
parametrized ...
Evaluation of parameterized quantum circuits: on the relation between classification accuracy, expressibility, and entangling capability
- 2021
AbstractAn 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 circuit to uniformly
address the Hilbe...
Decoding surface code with a distributed neural network–based decoder
Tập 2 Số 1 - 2020
AbstractThere 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 code under realistic noise
assumptio...
A continuous-variable quantum-inspired algorithm for classical image segmentation
Tập 1 Số 3-4 - Trang 97-111 - 2019
Binary classification with classical instances and quantum labels
Tập 3 Số 1 - 2021
AbstractIn 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 known to have the same sample
compl...
Huấn luyện mẫu boson Gauss bằng học máy lượng tử Dịch bởi AI
- 2021
Tóm tắtChúng tôi sử dụng mạng nơ-ron để biểu diễn hàm đặc trưng của các trạng
thái Gauss nhiều hạt trong không gian pha lượng tử. Bằng cơ chế kéo ngược, chúng
tôi mô hình hóa các phép biến đổi do các toán tử đơn vị tạo ra dưới dạng các lớp
tuyến tính có thể xếp chồng lên nhau để mô phỏng các quá trình đa hạt phức tạp.
Chúng tôi sử dụng các mạng nơ-ron nhiều lớp cho sự lan truyền ánh sáng phi cổ
đi...