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Books on the topic 'Extremes of Gaussian processes'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Hida, Takeyuki. Gaussian processes. Providence, R.I: American Mathematical Society, 1993.

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2

Hida, Takeyuki. Gaussian processes. Providence, R.I: American Mathematical Society, 1993.

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3

service), SpringerLink (Online, ed. Lectures on Gaussian Processes. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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4

Lifshits, Mikhail. Lectures on Gaussian Processes. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24939-6.

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5

Marcus, Michael B. Markov processes, Gaussian processes, and local times. New York: Cambridge University Press, 2006.

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6

I, Williams Christopher K., ed. Gaussian processes for machine learning. Cambridge, Mass: MIT Press, 2006.

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7

Rasmussen, Carl Edward. Gaussian processes for machine learning. Cambridge, MA: MIT Press, 2005.

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8

Nagoya Lévy Seminar (3rd 1990 Nagoya-shi, Japan). Gaussian random fields. Edited by Hida Takeyuki 1927-, Itō Kiyosi 1915-, International Conference on Gaussian Random Fields (1990 : Nagoya-shi, Japan), and International Congress of Mathematicians. (1990 : Kyoto, Japan). Singapore: World Scientific, 1991.

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9

Lifshit͡s, M. A. Gaussian random functions. Dordrecht: Kluwer Academic Publishers, 1995.

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10

S, Taqqu Murad, ed. Stable non-Gaussian random processes: Stochastic models with infinite variance. New York: Chapman & Hall, 1994.

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11

Lifshit︠s︡, M. A. Gaussovskie sluchaĭnye funkt︠s︡ii. Kiev: TViMS, 1995.

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12

Berman, Simeon M. Sojourns and extremes of stochastic processes. Pacific Grove, Calif: Wadsworth & Brooks/Cole Advanced Books & Software, 1992.

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13

Glonti, O. A. Issledovanii͡a︡ po teorii uslovno-gaussovskikh prot͡s︡essov. Tbilisi: Izd-vo "Met͡s︡niereba", 1985.

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14

Adler, Robert J. An introduction to continuity, extrema, and related topics for general Gaussian processes. Hayward, Calif: Institute of Mathematical Statistics, 1990.

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15

Das, Sanjiv R. Poisson-Gaussian processes and the bond markets. Cambridge, MA: National Bureau of Economic Research, 1998.

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16

Mannersalo, Petteri. Gaussian and multifractal processes in teletraffic theory. Espoo [Finland]: VTT Technical Research Centre of Finland, 2003.

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17

Frisch, Michael J. Gaussian 92 programmer's reference. Pittsburgh: Gaussian, Inc., 1993.

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18

Frisch, Michael J. Gaussian 92 user's guide. Pittsburgh: Gaussian, Inc., 1992.

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19

Leszek, Gawarecki, ed. Stochastic analysis for Gaussian random processes and fields: With applications. Boca Raton: CRC Press, Taylor & Francis Group, 2016.

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20

Ferraro, Alessandro. Gaussian states in quantum information. Napoli: Bibliopolis, 2005.

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21

Rosenblatt, Murray. Gaussian and Non-Gaussian Linear Time Series and Random Fields. New York, NY: Springer New York, 2000.

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22

Matthias, Richter. Approximation of Gaussian random elements and statistics. Stuttgart: B.G Teubner, 1992.

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23

Topics in occupation times and Gaussian free fields. Zürich, Switzerland: European Mathematical Society, 2012.

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24

Hough, J. Ben. Zeros of Gaussian analytic functions and determinantal point processes. Providence, R.I: American Mathematical Society, 2009.

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25

Taeryon, Choi, ed. Gaussian process regression analysis for functional data. Boca Raton, FL: CRC Press, 2011.

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26

Sporring, Jon. Gaussian Scale-Space Theory. Dordrecht: Springer Netherlands, 1997.

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27

Hemachandran, K., Shubham Tayal, Preetha Mary George, Parveen Singla, and Utku Kose. Bayesian Reasoning and Gaussian Processes for Machine Learning Applications. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003164265.

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28

Pipiras, Vladas, and Murad S. Taqqu. Stable Non-Gaussian Self-Similar Processes with Stationary Increments. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62331-3.

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29

David, Middleton. Non-Gaussian statistical communication theory. Hoboken, N.J: Wiley-IEEE Press, 2012.

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30

The Generic Chaining: Upper and Lower Bounds of Stochastic Processes (Springer Monographs in Mathematics). Springer, 2005.

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31

Buldygin, Valery V., and Kozachenko Yu V. Pre-Gaussian and Sub-Gaussian Processes. Amer Mathematical Society, 1999.

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32

Gaussian Random Processes. Springer, 2011.

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33

Aries, A. B. Gaussian Random Processes. Springer, 2011.

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34

Rozanov, Y. A., I. A. Ibragimov, and A. B. Aries. Gaussian Random Processes. Springer London, Limited, 2012.

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35

Rosen, Jay, and Michael Marcus. Markov Processes and Gaussian Processes. Cambridge University Press, 2008.

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36

Lifshits, Mikhail. Lectures on Gaussian Processes. Springer, 2012.

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37

Lifshits, Mikhail. Lectures on Gaussian Processes. Springer, 2012.

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38

Lifshits, M. A. Gaussian Random Functions. Springer, 2011.

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39

Xiao, Jie, Dachun Yang, Wen Yuan, and Liguang Liu. Gaussian Capacity Analysis. Springer, 2018.

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40

Rosen, Jay, and Michael B. Marcus. Markov Processes, Gaussian Processes, and Local Times. Cambridge University Press, 2011.

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41

Rosen, Jay, and Michael B. Marcus. Markov Processes, Gaussian Processes, and Local Times. Cambridge University Press, 2010.

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42

Rosen, Jay, and Michael B. Marcus. Markov Processes, Gaussian Processes, and Local Times. Cambridge University Press, 2006.

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43

Rasmussen, Carl Edward, Christopher K. I. Williams, and Francis Bach. Gaussian Processes for Machine Learning. MIT Press, 2005.

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44

Rasmussen, Carl Edward, Christopher K. I. Williams, and Francis Bach. Gaussian Processes for Machine Learning. MIT Press, 2005.

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45

Rasmussen, Carl Edward, and Christopher K. I. Williams. Gaussian Processes for Machine Learning. The MIT Press, 2005. http://dx.doi.org/10.7551/mitpress/3206.001.0001.

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46

Twenty Lectures about Gaussian Processes. Atlantic Financial Press, 2015.

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47

Rasmussen, Carl Edward, and Christopher K. I. Williams. Gaussian Processes for Machine Learning. MIT Press, 2018.

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48

Belyaev and Piterbart. Theory of Gaussian Processes and Fields. Amer Mathematical Society, 1995.

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49

Gaussian and Non-Gaussian Linear Time Series and Random Fields. Springer, 1999.

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50

(Editor), Robert Adler, Raya Feldman (Editor), and Murad Taqqu (Editor), eds. A Practical Guide to Heavy Tails: Statistical Techniques and Applications. Birkhäuser Boston, 1998.

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