Search: QNN — Academic Articles

QEKI: A Quantum–Classical Framework for Efficient Bayesian Inversion of PDEs

Jiawei Yong, Sihai Tang • Entropy (2026)

Solving Bayesian inverse problems efficiently stands as a major bottleneck in scientific computing. Although Bayesian Physics-Informed Neural Networks (B-PINNs) have introduced a robust way to quantify uncertainty, the high-dimensional para...

DOAJ Open Access (DOAJ) DOI: 10.3390/e28020156

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Quantum neural network

M. V. Altaĭsky • arXiv (Cornell University) (2001)

It is suggested that a quantum neural network (QNN), a type of artificial neural network, can be built using the principles of quantum information processing. The input and output qubits in the QNN can be implemented by optical modes with d...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.quant-ph/0107012

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Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El‐Yaniv et al. • arXiv (Cornell University) (2016)

We introduce a method to train Quantized Neural Networks (QNNs) --- neural networks with extremely low precision (e.g., 1-bit) weights and activations, at run-time. At train-time the quantized weights and activations are used for computing ...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1609.07061

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Bridging Deep Learning and Quantum Computing for EEG-Driven P300 Targeted ASD Response Detection

Sapthak Mohajon Turjya, Mulham Fawakherji • IEEE Access (2025)

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose diagnosis relies heavily on subjective behavioral assessments. Electroencephalography (EEG) provides an inexpensive and non-invasive method of objective biomarker detect...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3646589

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Framework for Implementing Quantum Neural Networks in Wireless Communications

Salik Siddiqui, Justin Holzer, Joshua Malcarne, Galahad M. B. Wernsing et al. • IEEE Access (2025)

While quantum computing is already being employed in different domains to solve large scale and highly complex optimization problems, the wireless communications community has only recently begun exploring the potential of Quantum Machine L...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3572416

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ℤ<sub>2</sub> × ℤ<sub>2</sub> Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks

Zhongtian Dong, Marçal Comajoan Cara, Gopal Ramesh Dahale, Roy T. Forestano et al. • Axioms (2024)

This paper presents a comparative analysis of the performance of Equivariant Quantum Neural Networks (EQNNs) and Quantum Neural Networks (QNNs), juxtaposed against their classical counterparts: Equivariant Neural Networks (ENNs) and Deep Ne...

DOAJ Open Access (DOAJ) DOI: 10.3390/axioms13030188

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Academic Articles & Research Papers

QEKI: A Quantum–Classical Framework for Efficient Bayesian Inversion of PDEs

Quantum neural network

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Bridging Deep Learning and Quantum Computing for EEG-Driven P300 Targeted ASD Response Detection

Framework for Implementing Quantum Neural Networks in Wireless Communications

ℤ<sub>2</sub> × ℤ<sub>2</sub> Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks