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A neural network model for survival data

David Faraggi, Richard M Simon • Statistics in Medicine (1995)

Neural networks have received considerable attention recently, mostly by non-statisticians. They are considered by many to be very promising tools for classification and prediction. In this paper we present an approach to modelling censored...

OPENALEX DOI: https://doi.org/10.1002/sim.4780140108

Hypergraph Neural Networks

Yifan Feng, Haoxuan You, Zizhao Zhang, Rongrong Ji et al. • Proceedings of the AAAI Conference on Artificial Intelligence (2019)

In this paper, we present a hypergraph neural networks (HGNN) framework for data representation learning, which can encode high-order data correlation in a hypergraph structure. Confronting the challenges of learning representation for comp...

OPENALEX Open Access DOI: https://doi.org/10.1609/aaai.v33i01.33013558

Applications of Neural Networks in Electromagnetics

Christos Christodoulou, Michael Georgiopoulos • CERN Document Server (European Organization for Nuclear Research) (2001)

From the Book: Since the early 1990s, a plethora of electromagnetic problems have been tackled using neural networks, some more successfully than others. Because neural networks and electromagnetics are two different scientific fields, not...

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An Introduction to Convolutional Neural Networks

Aarush Saxena • International Journal for Research in Applied Science and Engineering Technology (2022)

Abstract: The field of machine learning has taken a dramatic twist in re- cent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models can far exceed the per- performance of previous for...

OPENALEX Open Access DOI: https://doi.org/10.22214/ijraset.2022.47789

Pulsed Neural Networks

• The MIT Press eBooks (1998)

Most practical applications of artificial neural networks are based on a computational model involving the propagation of continuous variables from one processing unit to the next. In recent years, data from neurobiological experiments have...

OPENALEX DOI: https://doi.org/10.7551/mitpress/5704.001.0001

cuDNN: Efficient Primitives for Deep Learning

Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Cohen, Jonathan et al. • arXiv (Cornell University) (2014)

We present a library of efficient implementations of deep learning primitives. Deep learning workloads are computationally intensive, and optimizing their kernels is difficult and time-consuming. As parallel architectures evolve, kernels mu...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1410.0759

PG-MACO Optimization Method for Ship Pipeline Layout

LIN Yan, JIN Tingyu, YANG Yuchao • Shanghai Jiaotong Daxue xuebao (2024)

Aimed at the problem of low efficiency of ship pipeline design, an optimization method of pipeline layout is proposed. An optimization mathematical model is established by comprehensively considering the engineering background of safety, ec...

DOAJ Open Access (DOAJ) DOI: 10.16183/j.cnki.jsjtu.2022.508

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

Challenges in automotive software engineering

Manfred Broy • ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) (2006)

The amount of software in cars grows exponentially. Driving forces of this development are cheaper and more powerful hardware and the demand for innovations by new functions. The rapid increase of software and software based functionality b...

OPENALEX DOI: https://doi.org/10.1145/1134285.1134292

Default Detection Rate-Dependent Software Reliability Model with Imperfect Debugging

Ce Zhang, Wei-Gong Lv, Sheng Sheng, Jin-Yong Wang et al. • Applied Sciences (2022)

From the perspective of FDR (fault detection rate), which is an indispensable component in reliability modeling, this paper proposes two kinds of reliability models under imperfect debugging. This model is a relatively flexible and unified ...

DOAJ Open Access (DOAJ) DOI: 10.3390/app122110736

Spreading Social Influence with both Positive and Negative Opinions in Online Networks

Jing (Selena) He, Meng Han, Shouling Ji, Tianyu Du et al. • Big Data Mining and Analytics (2019)

Social networks are important media for spreading information, ideas, and influence among individuals. Most existing research focuses on understanding the characteristics of social networks, investigating how information is spread through t...

DOAJ Open Access (DOAJ) DOI: 10.26599/BDMA.2018.9020034

Application of Robust Estimation for Time Synchronization and Retaining in Local Area Network

LIAN Yueyong,ZHANG Chao,LI Qiang • Jisuanji gongcheng (2016)

In view of the defect existed in the time synchronization of Local Area Network(LAN) using hardware and software methods,this paper introduces the principle of time synchronization in LAN and the method of robust estimation.The model of tim...

DOAJ Open Access (DOAJ) DOI: 10.3969/j.issn.1000-3428.2016.02.051

Software Engineering in the Small.

Mohamed E. Fayad • UCLA - Biblioteca de Ciencias y Tecnologia Felix Morales Bueno

The article focuses on issues concerning software engineering The article focuses on issues concerning software engineering. Smaller-sized software companies are developing significant products that need effective, tailored software ...

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Essentials of Software Engineering

Frank F. Tsui, Orlando Karam, Barbara Bernal (2006)

"The basic concepts and theories of software engineering have stabilized considerably from the early days of thirty to forty years ago. Nevertheless, the technology and tools continue to evolve, expand and improve every four to five years. ...

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