A Comparative Study of Inductive and Transductive Learning with Feedforward Neural Networks

AI*IA 2016 Advances in Artificial Intelligence - Lecture Notes in Computer Science ◽

10.1007/978-3-319-49130-1_21 ◽

2016 ◽

pp. 283-293 ◽

Author(s):

Monica Bianchini ◽

Anas Belahcen ◽

Franco Scarselli

Keyword(s):

Neural Networks ◽

Comparative Study ◽

Feedforward Neural Networks ◽

Transductive Learning

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A comparative study of the ids method and feedforward neural networks

Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. ◽

10.1109/ijcnn.2005.1556149 ◽

2006 ◽

Author(s):

M. Murakami ◽

N. Honda

Keyword(s):

Neural Networks ◽

Comparative Study ◽

Feedforward Neural Networks

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Solving a Combinatorial Optimization Problem with Feedforward Neural Networks

1993 American Control Conference ◽

10.23919/acc.1993.4793106 ◽

1993 ◽

Author(s):

Xianzhong Cui ◽

Kang G. Shin

Keyword(s):

Neural Networks ◽

Combinatorial Optimization ◽

Optimization Problem ◽

Feedforward Neural Networks ◽

Combinatorial Optimization Problem

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Effect of inhibitory firing patterns on information transmission in feedforward neural networks

2019 Chinese Control Conference (CCC) ◽

10.23919/chicc.2019.8865330 ◽

2019 ◽

Author(s):

Pengzhen Zhang ◽

Bin Deng ◽

Xinmeng Guo ◽

Jiang Wang ◽

Haitao Yu

Keyword(s):

Neural Networks ◽

Information Transmission ◽

Feedforward Neural Networks ◽

Firing Patterns

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Comparative study for load forecasting using artificial neural networks “ANN” and a statistical package

3rd International Conference on Advances in Power System Control, Operation and Management (APSCOM 95) ◽

10.1049/cp:19951275 ◽

1995 ◽

Author(s):

M.M. Elkateb

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Comparative Study ◽

Load Forecasting ◽

Artificial Neural

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Artificial Neural Networks for (Automotive) Embedded Control - A Comparative Study

2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC) ◽

10.1109/ccwc51732.2021.9376085 ◽

2021 ◽

Author(s):

Sven Dominka ◽

Henrik Smith ◽

Benjamin Hartmann

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Comparative Study ◽

Embedded Control ◽

Artificial Neural

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Asymptotic Prediction Error Variance for Feedforward Neural Networks

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2020.12.1310 ◽

2020 ◽

Vol 53 (2) ◽

pp. 1108-1113

Author(s):

Magnus Malmström ◽

Isaac Skog ◽

Daniel Axehill ◽

Fredrik Gustafsson

Keyword(s):

Neural Networks ◽

Prediction Error ◽

Feedforward Neural Networks ◽

Error Variance ◽

Prediction Error Variance

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Improved remote-sensing land cover identification using parameterized feedforward neural networks

Euro-Mediterranean Journal for Environmental Integration ◽

10.1007/s41207-020-00226-3 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Olfa Charfi Marrakchi

Keyword(s):

Remote Sensing ◽

Neural Networks ◽

Feedforward Neural Networks

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On Inductive-Transductive Learning with Graph Neural Networks

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/tpami.2021.3054304 ◽

2021 ◽

pp. 1-1

Author(s):

Giorgio Ciano ◽

Alberto Rossi ◽

Monica Bianchini ◽

Franco Scarselli

Keyword(s):

Neural Networks ◽

Transductive Learning ◽

Graph Neural Networks

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A Comparative Study of 1D-Convolutional Neural Networks with Modified Possibilistic c-Mean Algorithm for Mapping Transplanted Paddy Fields Using Temporal Data

Journal of the Indian Society of Remote Sensing ◽

10.1007/s12524-020-01303-4 ◽

2021 ◽

Author(s):

Anuvi Rawat ◽

Anil Kumar ◽

Priyadarshi Upadhyay ◽

Shashi Kumar

Keyword(s):

Neural Networks ◽

Comparative Study ◽

Convolutional Neural Networks ◽

Paddy Fields ◽

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A hybrid computational intelligence approach for structural damage detection using marine predator algorithm and feedforward neural networks

Computers & Structures ◽

10.1016/j.compstruc.2021.106568 ◽

2021 ◽

Vol 252 ◽

pp. 106568

Author(s):

Long Viet Ho ◽

Duong Huong Nguyen ◽

Mohsen Mousavi ◽

Guido De Roeck ◽

Thanh Bui-Tien ◽

...

Keyword(s):

Neural Networks ◽

Damage Detection ◽

Computational Intelligence ◽

Structural Damage ◽

Feedforward Neural Networks ◽

Structural Damage Detection ◽

Marine Predator ◽

Intelligence Approach

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