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Showing 20 of 785 academic articles

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

Introduction to Neural Networks.

Nanette S. Holder • Defense Technical Information Center (DTIC) (1992)

1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks....

OPENALEX Open Access DOI: https://doi.org/10.21236/ada248258

Applied Deep Learning

Umberto Michelucci • Apress eBooks (2018)

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks, in this compr...

OPENALEX Open Access DOI: https://doi.org/10.1007/978-1-4842-3790-8

EdgeAIGC: Model caching and resource allocation for edge artificial intelligence generated content

Wu Wen, Yibin Huang, Xinxin Zhao, Peiying Zhang et al. • Digital Communications and Networks (2025)

With the rapid development of generative artificial intelligence technology, the traditional cloud-based centralized model training and inference face significant limitations due to high transmission latency and costs, which restrict user-s...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dcan.2025.07.003

High Energy Astrophysics

Malcolm S. Longair • Cambridge University Press eBooks (1994)

What role does viscosity play in accretion discs? How do you calculate the 'glitch function' of a pulsar? And can strong shocks account for the energy spectrum of electrons in our Galaxy? These are just some of the exciting questions that P...

OPENALEX DOI: https://doi.org/10.1017/cbo9781139170505

Enhancing Psychiatry Training Using an Agentic AI Simulated Consultation Tool: Prospective Cohort Study

Alice Rueda, Huda F Al-Shamali, Zack Cote, Niloy Roy et al. • JMIR Medical Education (2026)

Abstract BackgroundCanadian psychiatry residents must demonstrate consultation competency, assessed using the standardized assessment of a clinical encounter report (STACER). However, opportunities to practice these skills and r...

DOAJ Open Access (DOAJ) DOI: 10.2196/88580

Evaluation of the implementation of International Classification of Diseases, 11th revision for morbidity coding: Rationale and study protocol

Reza Golpira, Zahra Azadmanjir, Javad Zarei, Nasim Hashemi et al. • Informatics in Medicine Unlocked (2021)

International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) has been used for many years in many countries to manage health information. The World Health Organization (WHO) will soon replace ICD-...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.imu.2021.100668

Development and validation of an online dynamic nomogram based on the atherogenic index of plasma to screen nonalcoholic fatty liver disease

Hewei Peng, Junchao Zhang, Xianhua Huang, Miao Xu et al. • Lipids in Health and Disease (2023)

Abstract Background Nonalcoholic fatty liver disease (NAFLD), a common liver disease worldwide, can be reversed early in life with lifestyle and medical interventions. This study aimed to develop a noninvasive tool to screen NAFLD accuratel...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12944-023-01808-0

Educational Institutions of Labor Reserves in Western Siberia at the Beginning of the Great Patriotic War (1941–1942)

I. G. Dokuchaeva • Вестник Кемеровского государственного университета (2019)

The evacuation of industrial enterprises, educational institutions, and millions of Soviet citizens during the Great Patriotic War is a tragic page in the history of Russia. This complex operation involved the evacuation and placement of hu...

DOAJ Open Access (DOAJ) DOI: 10.21603/2078-8975-2019-21-3-585-594

Renewable Energy Resources

John Twidell, Tony Weir • Routledge eBooks (2015)

Renewable Energy Resources is a numerate and quantitative text covering the full range of renewable energy technologies and their implementation worldwide. Energy supplies from renewables (such as from biofuels, solar heat, photovoltaics, w...

OPENALEX DOI: https://doi.org/10.4324/9781315766416

Achieving high thermal conductivity of Al–50Si alloy through heat treatment and its microstructural evolution

Chao Ding, Huali Hao, Rui Ma, Changqing Ye et al. • Journal of Materials Research and Technology (2023)

Al–50Si alloys were prepared by powder extrusion and characterized for electronic packaging. The optimization of powder size, extrusion temperature, and heat treatment parameters was performed to enhance the microstructure and thermo-physic...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jmrt.2023.11.038

Expressibility and trainability of parametrized analog quantum systems for machine learning applications

Jirawat Tangpanitanon, Supanut Thanasilp, Ninnat Dangniam, Marc-Antoine Lemonde et al. • Physical Review Research (2020)

Parametrized quantum evolution is the main ingredient in variational quantum algorithms for near-term quantum devices. In digital quantum computing, it has been shown that random parametrized quantum circuits are able to express complex dis...

DOAJ Open Access (DOAJ) DOI: 10.1103/PhysRevResearch.2.043364

An introduction to Bayesian simulation-based inference for quantum machine learning with examples

Ivana Nikoloska, Osvaldo Simeone • Frontiers in Quantum Science and Technology (2024)

Simulation is an indispensable tool in both engineering and the sciences. In simulation-based modeling, a parametric simulator is adopted as a mechanistic model of a physical system. The problem of designing algorithms that optimize the sim...

DOAJ Open Access (DOAJ) DOI: 10.3389/frqst.2024.1394533

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

Exploiting subspace constraints and ab initio variational methods for quantum chemistry

Cica Gustiani, Richard Meister, Simon C Benjamin • New Journal of Physics (2023)

Variational methods offer a highly promising route to exploiting quantum computers for chemistry tasks. Here we employ methods described in a sister paper to the present report, entitled exploring ab initio machine synthesis of quantum circ...

DOAJ Open Access (DOAJ) DOI: 10.1088/1367-2630/ace182

Magnetic field reconstruction from proton radiography via physics-guided out-of-distribution filtering

Chun-Sung Jao, Chiung-Yin Chang, Kun-Han Lee, Hsiao-Hsuan Lin et al. • APL Machine Learning (2026)

Reconstructing multidimensional vector fields from path-integrated projection data is a fundamental challenge in high-energy-density physics, particularly when experimental sources exhibit spectral broadening and shot-to-shot jitter. We pre...

DOAJ Open Access (DOAJ) DOI: 10.1063/5.0331075