Search Results - Quantum autoencoder*

Quantum Autoencoders to Denoise Quantum Data by Bondarenko, Dmytro, Feldmann, Polina

“… We develop a novel quantum autoencoder that successfully denoises Greenberger-Horne-Zeilinger, W, Dicke, and cluster states subject to spin-flip errors and random unitary noise…”
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Quantum Error Correction with Quantum Autoencoders by Locher, David F., Cardarelli, Lorenzo, Müller, Markus

“… Specifically, we demonstrate how quantum neural networks, in the form of quantum autoencoders, can be trained to learn optimal strategies for active detection and correction of errors, including…”
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Anomaly detection in high-energy physics using a quantum autoencoder by Ngairangbam, Vishal S., Spannowsky, Michael, Takeuchi, Michihisa

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Quantum Autoencoders for Learning Quantum Channel Codes by Rathi, Lakshika, DiAdamo, Stephen, Shabani, Alireza

“…This work investigates the application of quantum machine learning techniques for classical and quantum communication across different qubit channel models…”
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Denoising quantum mixed states using quantum autoencoders by Wang, Ming-Ming

“…The presence of noise affects the process of quantum computing and quantum communication, and quantum autoencoders (QAEs…”
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Experimental Realization of a Quantum Autoencoder: The Compression of Qutrits via Machine Learning by Pepper, Alex, Tischler, Nora, Pryde, Geoff J.

“… Quantum autoencoders have been proposed as a way to reduce quantum memory requirements. Generally, an autoencoder is a device that uses machine learning to compress inputs, that is, to represent the input data in a lower-dimensional space…”
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Hybrid classical-quantum autoencoder for anomaly detection by Sakhnenko, Alona, O’Meara, Corey, Ghosh, Kumar J. B., Mendl, Christian B., Cortiana, Giorgio, Bernabé-Moreno, Juan

“…We propose a hybrid classical-quantum autoencoder (HAE) model, which is a synergy of a classical autoencoder (AE…”
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Quantum autoencoders with enhanced data encoding by Bravo-Prieto, Carlos

“…We present the enhanced feature quantum autoencoder, or EF-QAE, a variational quantum algorithm capable of compressing quantum states of different models with higher fidelity…”
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Error mitigation in brainbox quantum autoencoders by Pazem, Joséphine, Ansari, Mohammad H.

“… Quantum autoencoder circuits with a single qubit bottleneck have demonstrated the capability to correct errors in noisy entangled states…”
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Quantum autoencoder implementation of high-dimensional steganographic encoding for arbitrary quantum states by Hao, Chaolong, Ma, Quangong, Chen, Yaqi, Zhang, Hao, Qu, Dan

“… We progressively explore Quantum Autoencoder (QAE) structures through three stages: starting from single-state scenarios without perturbation, advancing to perturbed conditions, and finally extending to multi-state tasks…”
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Resource-efficient high-dimensional subspace teleportation with a quantum autoencoder by Zhang, Hui, Wan, Lingxiao, Haug, Tobias, Mok, Wai-Keong, Paesani, Stefano, Shi, Yuzhi, Cai, Hong, Chin, Lip Ket, Karim, Muhammad Faeyz, Xiao, Limin, Luo, Xianshu, Gao, Feng, Dong, Bin, Assad, Syed, Kim, M. S., Laing, Anthony, Kwek, Leong Chuan, Liu, Ai Qun

“…Quantum autoencoders serve as efficient means for quantum data compression. Here, we propose and demonstrate their use to reduce resource costs for quantum teleportation of subspaces in high-dimensional systems…”
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On compression rate of quantum autoencoders: Control design, numerical and experimental realization by Ma, Hailan, Huang, Chang-Jiang, Chen, Chunlin, Dong, Daoyi, Wang, Yuanlong, Wu, Re-Bing, Xiang, Guo-Yong

“…Quantum autoencoders which aim at compressing quantum information in a low-dimensional latent space lie in the heart of automatic data compression in the field of quantum information…”
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Quantum autoencoders for image classification by Asaoka, Hinako, Kudo, Kazue

“… In contrast to QCNNs, quantum autoencoders (QAEs) leverage classical optimization solely for parameter tuning…”
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A black-box attack method of machine learning algorithms based on quantum autoencoders by Tan, Dong, Yan, Lili, Zhao, Jiayu, Chang, Yan, Zhang, Shibin

“… This paper proposes a new black-box attack method against quantum machine learning models based on a quantum autoencoder (QAE…”
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Clustering and enhanced classification using a hybrid quantum autoencoder by Srikumar, Maiyuren, Hill, Charles D, Hollenberg, Lloyd C L

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Unsupervised beyond-standard-model event discovery at the LHC with a novel quantum autoencoder by Duffy, Callum, Hassanshahi, Mohammad, Jastrzebski, Marcin, Malik, Sarah

“… We introduce a novel quantum autoencoder circuit ansatz that is specifically designed for this task and demonstrates superior performance compared to previous approaches…”
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Quantum autoencoders for communication-efficient cloud computing by Zhu, Yan, Bai, Ge, Wang, Yuexuan, Li, Tongyang, Chiribella, Giulio

“… Here we propose quantum autoencoders for quantum gates (QAEGate) as a method for compressing quantum computations…”
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Applying quantum autoencoders for time series anomaly detection by Frehner, Robin, Stockinger, Kurt

“… This paper explores the application of quantum autoencoders to time series anomaly detection…”
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Efficient Data Loading with Quantum Autoencoder by Wu, Siang-Ruei, Li, Chun-Tse, Cheng, Hao-Chung

“… In this work, we propose an efficient quantum autoencoder architecture that can construct a quantum state approximating the unknown classical distribution with high precision and with only linear circuit depth…”
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Quantum Autoencoder for Enhanced Fraud Detection in Imbalanced Credit Card Dataset by Huot, Chansreynich, Heng, Sovanmonynuth, Kim, Tae-Kyung, Han, Youngsun

“… In response to these challenges, we propose a novel detection model utilizing Quantum AutoEncoders-based Fraud Detection (QAE-FD…”
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