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Books on the topic 'Neural networks (Computer science) Statistical mechanics'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

F, De Groff Dolores, ed. Neural network modeling: Statistical mechanics and cybernetic perspectives. Boca Raton, Fla: CRC Press, 1994.

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2

Davino, Cristina, and Salvatore Ingrassia. Reti neuronali e metodi statistici. Milano: F. Angeli, 2002.

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3

An introduction to the theory of spin glasses and neural networks. Singapore: World Scientific, 1994.

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4

Jong-Hoon, Oh, Kwon Chulan, Cho Sungzoon, Sŏul Taehakkyo. Chayŏn Kwahak Taehak. Pusŏl Iron Mullihak Yŏnʼguso., and Pʻohang Kongkwa Taehak (Korea). Kichʻo Kwahak Yŏnʼguso., eds. Neural networks: The statistical mechanics perspective : proceedings of the CTP-PBSRI Joint Workshop on Theoretical Physics, POSTECH, Pohang, Korea, 2-4 February 95. Singapore: World Scientific, 1995.

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5

Neural networks for statistical modeling. New York: Van Nostrand Reinhold, 1993.

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6

Theoretical mechanics of biological neural networks. Boston: Academic Press, 1993.

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7

Neal, Radford M. Bayesian learning for neural networks. New York: Springer, 1996.

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8

Neal, Radford M. Bayesian learning for neural networks. Toronto: University of Toronto, Dept. of Computer Science, 1995.

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9

M, Noble John, ed. Bayesian networks: An introduction. Hoboken, NJ: John Wiley & Sons, 2009.

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10

Koski, Timo. Bayesian networks: An introduction. Chichester, West Sussex, UK: Wiley, 2009.

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11

Statistical and neural classifiers: An integrated approach to design. London: Springer, 2001.

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12

Jinqing, Fang, ed. Wang luo ke xue yu tong ji wu li fang fa. Beijing Shi: Beijing da xue chu ban she, 2011.

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13

Müller, Berndt. Neural networks: An introduction. 2nd ed. Berlin: Springer, 1995.

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14

Müller, Berndt. Neural networks: An introduction. 2nd ed. Berlin: Springer-Verlag, 1991.

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15

1952-, Reinhardt J., ed. Neural networks: An introduction. Berlin: Springer-Verlag, 1990.

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16

Learning Bayesian networks. Harlow: Prentice Hall, 2003.

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17

Neapolitan, Richard E. Learning Bayesian networks. Upper Saddle River, NJ: Pearson Prentice Hall, 2004.

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18

Pattern classification: A unified view of statistical and neural approaches. New York: Wiley, 1996.

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19

Approximation methods for efficient learning of Bayesian networks. Amsterdam: IOS Press, 2008.

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20

Jensen, Finn V. An introduction to Bayesian networks. New York: Springer, 1996.

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21

Jensen, Finn V. An introduction to Bayesian networks. London: UCL Press, 1996.

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22

Rittinghaus-Meyer, Diana. Die Anwendung von neuronalen Netzen in der Marketingforschung. München: Akademischer Verlag, 1993.

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23

Intelligent systems and signal processing in power engineering. Germany [1990-onward]: Springer Verlag, 2007.

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24

Focus, Symposium on Learning and Adaptation in Stochastic and Statistical Systems (2001 Baden-Baden Germany). Proceedings of the Focus Symposium on Learning and Adaptation in Stochastic and Statistical Systems. Windsor, Ont: International Institute for Advanced Studies in Systems Research and Cybernetics, 2002.

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25

Ukil, Abhisek. Intelligent systems and signal processing in power engineering. Berlin: Springer Verlag, 2007.

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26

1941-, Johnsonbaugh Richard, and Jost Steve, eds. Pattern recognition and image analysis. Upper Saddle River, NJ: Prentice Hall PTR, 1996.

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27

Lopez, Damian. Seismic classification of military vehicles using statistical pattern recognition. Bochum: UVB Universitätsverlag Dr. N. Brockmeyer, 1995.

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28

Ayyub, Bilal M. Uncertainty analysis in engineering and sciences: Fuzzy logic, statistics, and neural network approach. Boston: Kluwer Academic Publishers, 1997.

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29

Tulupʹev, A. L. Baĭesovskie seti: Logiko-veroi︠a︡tnostnyĭ podkhod. Sankt-Peterburg: "Nauka", 2006.

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30

E, Nicholson Ann, ed. Bayesian artificial intelligence. Boca Raton, Fla: Chapman & Hall/CRC, 2004.

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31

Grima, Mario Alvarez. Neuro-fuzzy modeling in engineering geology: Applications to mechanical rock excavation, rock strength estimation, and geological mapping. Rotterdam: A.A. Balkema, 2000.

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32

Bayesian networks and decision graphs. New York: Springer, 2001.

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33

Beiyesi wang luo li lun ji qi zai jun shi xi tong zhong de ying yong. Beijing Shi: Guo fang gong ye chu ban she, 2012.

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34

Snail, Mgebwi Lavin. The antecedens [sic] and the emergence of the black consciousness movement in South Africa: Its ideology and organisation. München: Akademischer Verlag, 1993.

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35

E, Nicholson Ann, ed. Bayesian artificial intelligence. 2nd ed. Boca Raton, FL: CRC Press, 2011.

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36

Statistical Mechanics of Learning. Cambridge University Press, 2001.

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37

1930-, Garrido L., ed. Statistical mechanics of neural networks: Proceedings of the XIth Sitges conference, Sitges, Barcelona, Spain, 3-7 June 1990. Berlin: Springer-Verlag, 1990.

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38

Swamy, M. N. S., and Ke-Lin Du. Neural Networks and Statistical Learning. Springer, 2013.

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39

Swamy, M. N. S., and Ke-Lin Du. Neural Networks and Statistical Learning. Springer, 2019.

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40

Swamy, M. N. S., and Ke-Lin Du. Neural Networks and Statistical Learning. Springer, 2013.

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41

Kolossa, Antonio. Computational Modeling of Neural Activities for Statistical Inference. Springer, 2016.

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42

Kolossa, Antonio. Computational Modeling of Neural Activities for Statistical Inference. Springer, 2018.

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43

Huang, Su-Yun. Statistical Learning: Building Knowledge from Data. Wiley & Sons, Incorporated, John, 2014.

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44

1931-, Haykin Simon S., ed. New directions in statistical signal processing: From systems to brain. Cambridge, Mass: MIT Press, 2006.

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45

Laszlo, Berke, and United States. National Aeronautics and Space Administration., eds. Functional approximation using artificial neural networks in structural mechanics. [Washington, DC]: National Aeronautics and Space Administration, 1993.

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46

(Editor), J. W. Kay, and D. M. Titterington (Editor), eds. Statistics and Neural Networks: Advances at the Interface (Royal Statistical Society Lecture Notes Series, 5). Oxford University Press, USA, 2000.

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47

Statistical methods and neural network approaches for classification of data from multiple sources. West Lafayette, Ind: Laboratory for Applications of Remote Sensing, 1990.

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48

(Editor), Simon Haykin, José C. Príncipe (Editor), Terrence J. Sejnowski (Editor), and John McWhirter (Editor), eds. New Directions in Statistical Signal Processing: From Systems to Brains (Neural Information Processing). The MIT Press, 2006.

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49

Tirozzi, Brunello, Silvia Puca, and Stefano Pittalis. Neural Networks and Sea Time Series. Springer, 2008.

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50

Müller, Berndt, and Joachim Reinhardt. Neural Networks: An Introduction (Physics of Neural Networks). Springer, 1991.

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