Search Results - "Quantum autoencoder"

Quantum-Classical Autoencoder Architectures for End-to-End Radio Communication

Authors: Zsolt I. Tabi Bence Bakó Dániel T. R. Nagy et al.

Contributors: Zsolt I. Tabi Bence Bakó Dániel T. R. Nagy et al.

Source: IEEE Access, Vol 13, Pp 82181-82192 (2025)

Subject Terms: Quantum circuit, Quantum Physics, 9. Industry and infrastructure, Radio communication, Adaptation models, FOS: Physical sciences, Quantum autoencoder, Autoencoders, Receivers, Symbols, TK1-9971, Physical sciences, radio communication, Encoding, Machine learning, Computer architecture, Electrical engineering. Electronics. Nuclear engineering, Quantum Physics (quant-ph), quantum autoencoder, Neural networks, Quantum machine learning

File Description: application/pdf

Access URL: http://arxiv.org/abs/2405.18105
https://doaj.org/article/9ea1a04e0c2147e49ab3c314e82c0240
http://hdl.handle.net/10138/596697

Quantum deep learning-enhanced ethereum blockchain for cloud security: intrusion detection, fraud prevention, and secure data migration

Authors: A. Venkata Nagarjun Sujatha Rajkumar

Source: Scientific Reports, Vol 15, Iss 1, Pp 1-21 (2025)

Subject Terms: Adaptive intrusion detection, Cloud data transfer, Deep learning, Ethereum blockchain security, Quantum autoencoder, Smart contracts, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/570602e855614174a59840310442ee7c

Quantum autoencoder implementation of high-dimensional steganographic encoding for arbitrary quantum states

Authors: Chaolong Hao Quangong Ma Yaqi Chen et al.

Source: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 8, Pp 1-20 (2025)

Subject Terms: Quantum information hiding, Arbitrary states, High-dimensional entangled state, Quantum autoencoder, Orthogonal projection splitting structure, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://doaj.org/toc/1319-1578; https://doaj.org/toc/2213-1248

Access URL: https://doaj.org/article/7b0056ab058648e4bde431344a3d462c

Applying quantum autoencoders for time series anomaly detection

Authors: Frehner, Robin Stockinger, Kurt

Source: Quantum Machine Intelligence. 7

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Quantum Physics, Computer Science - Artificial Intelligence, Computer Science - Emerging Technologies, FOS: Physical sciences, Quantum autoencoder, Quantum computing, 006: Spezielle Computerverfahren, Machine Learning (cs.LG), Artificial Intelligence (cs.AI), Emerging Technologies (cs.ET), Time series anomaly detection, Quantum Physics (quant-ph), Quantum machine learning

Access URL: http://arxiv.org/abs/2410.04154

Quantum Autoencoder for Enhanced Fraud Detection in Imbalanced Credit Card Dataset

Authors: Chansreynich Huot Sovanmonynuth Heng Tae-Kyung Kim et al.

Source: IEEE Access, Vol 12, Pp 169671-169682 (2024)

Subject Terms: quantum machine learning (QML), imbalanced dataset, credit card fraud detection, Anomaly detection, Electrical engineering. Electronics. Nuclear engineering, quantum autoencoder (QAE), TK1-9971

Access URL: https://doaj.org/article/cc52584f1e7645e89b464d84a5219d9b

Quantum neural network autoencoder and classifier applied to an industrial case study

Authors: Stefano Mangini Alessia Marruzzo Marco Piantanida et al.

Contributors: Stefano Mangini Alessia Marruzzo Marco Piantanida et al.

Source: Quantum Machine Intelligence (Online) 4 (2022): 13-1–13-13. doi:10.1007/s42484-022-00070-4
info:cnr-pdr/source/autori:Mangini S.; Marruzzo A.; Piantanida M.; Gerace D.; Bajoni D.; Macchiavello C./titolo:Quantum neural network autoencoder and classifier applied to an industrial case study/doi:10.1007%2Fs42484-022-00070-4/rivista:Quantum Machine Intelligence (Online)/anno:2022/pagina_da:13-1/pagina_a:13-13/intervallo_pagine:13-1–13-13/volume:4

Subject Terms: FOS: Computer and information sciences, Quantum Physics, Computer Science - Machine Learning, FOS: Physical sciences, Quantum autoencoder, Quantum data analysi, Quantum machine learning, Industrial case study, Classification, Quantum data analysis, 01 natural sciences, Machine Learning (cs.LG), 0103 physical sciences, Quantum Physics (quant-ph)

File Description: application/pdf; ELETTRONICO

Access URL: http://arxiv.org/abs/2205.04127
https://hdl.handle.net/20.500.14243/446338
https://doi.org/10.1007/s42484-022-00070-4
https://link.springer.com/article/10.1007/s42484-022-00070-4

QUANTUM GRAPH NEURAL NETWORKS FOR TIME PROPAGATION IN CONDENSED MATTER

Authors: Yurtseven, Kaan Malcıoğlu, Osman Barış Department of Physics et al.

Contributors: Yurtseven, Kaan Malcıoğlu, Osman Barış Department of Physics et al.

Subject Terms: Quantum Autoencoder, Quantum Graph Neural Networks, Time-evolution, Fermi-Hubbard Model, Majonara Hubbard Model

File Description: application/pdf

Access URL: https://hdl.handle.net/11511/111493

Quantum Patch-Based Autoencoder for Anomaly Segmentation

Authors: Madeira, Maria Francisca Poggiali, Alessandro Lorenz, Jeanette Miriam

Contributors: Madeira, Maria Francisca Poggiali, Alessandro Lorenz, Jeanette Miriam

Subject Terms: Anomaly Segmen-tation, Quantum Autoencoder, Quantum Machine Learning

Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001438831500029; ispartofbook:Proceedings - IEEE Quantum Week 2024, QCE 2024; 5th IEEE International Conference on Quantum Computing and Engineering, QCE 2024; volume:1; firstpage:259; lastpage:267; numberofpages:9; https://hdl.handle.net/11568/1323191

Availability: https://hdl.handle.net/11568/1323191
https://doi.org/10.1109/qce60285.2024.00039

QUANTUM GRAPH NEURAL NETWORKS FOR TIME PROPAGATION IN CONDENSED MATTER ; YOĞUN MADDE İÇİNDE ZAMAN YAYILIMI İÇİN KUANTUM GRAFİK SİNİR AĞLARI

Authors: Yurtseven, Kaan Malcıoğlu, Osman Barış Department of Physics

Contributors: Yurtseven, Kaan Malcıoğlu, Osman Barış Department of Physics

Subject Terms: Quantum Autoencoder, Quantum Graph Neural Networks, Time-evolution, Fermi-Hubbard Model, Majonara Hubbard Model, Arbis Subjects::Natural Sciences

File Description: application/pdf

Relation: https://hdl.handle.net/11511/111493

Availability: https://hdl.handle.net/11511/111493

Development of convolution filter embedded quantum autoencoder by quantum simulator / 量子シミュレーターを畳み込み型量子自己符号化器の開発

Authors: Hiroto HAKAMATA Katsuhisa SAKAMOTO Kouichi YAMAGUCHI et al.

Source: Proceedings of the Annual Conference of JSAI. 2019, :2

Unsupervised beyond-standard-model event discovery at the LHC with a novel quantum autoencoder.

Authors: Duffy C Hassanshahi M Jastrzebski M et al.

Source: Quantum machine intelligence [Quantum Mach Intell] 2025; Vol. 7 (1), pp. 41. Date of Electronic Publication: 2025 Mar 15.

Publication Type: Journal Article

Journal Info: Publisher: Springer International Publishing Country of Publication: Switzerland NLM ID: 101770667 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2524-4914 (Electronic) Linking ISSN: 25244906 NLM ISO Abbreviation: Quantum Mach Intell Subsets: PubMed not MEDLINE