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bibliography.bib
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title={Probability theory: a comprehensive course},
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@book{tao2011introduction,
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@article{goldberger2000physiobank,
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@article{schalk2004bci2000,
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@misc{Dua:2019,
author="Dua, Dheeru and Graff, Casey",
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title="{UCI} Machine Learning Repository",
url="http://archive.ics.uci.edu/ml",
institution="University of California, Irvine, School of Information and Computer Sciences"
}
@article{chattopadhyay2014data,
title={Data smashing: uncovering lurking order in data},
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year={2014},
publisher={The Royal Society}
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@article{chattopadhyay2013abductive,
title={Abductive learning of quantized stochastic processes with probabilistic finite automata},
author={Chattopadhyay, Ishanu and Lipson, Hod},
journal={Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
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@article{chattopadhyay2014causality,
title={Causality networks},
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title={Probability, random variables, and random signal principles},
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@article{crutchfield1994calculi,
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@article{chattopadhyay2008structural,
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@book{gagniuc2017markov,
title={Markov chains: from theory to implementation and experimentation},
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year={2017},
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@article{bondy2008graph,
title={Graph theory (2008)},
author={Bondy, JA and Murty, USR},
journal={Grad. Texts in Math},
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@book{yan1998introductionMachineComputation,
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@article{stamp2004revealing,
title={A revealing introduction to hidden Markov models},
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@book{kai1967markov_StDis,
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@book{cover2012elements,
title={Elements of information theory},
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@article{matthews2016sparse,
title={On sparse variational methods and the Kullback-Leibler divergence between stochastic processes},
author={Matthews, Alexander G de G and Hensman, James and Turner, Richard and Ghahramani, Zoubin},
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}
@book{ray2012graph,
title={Graph theory with algorithms and its applications: in applied science and technology},
author={Ray, Santanu Saha},
year={2012},
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@book{doob1990stochastic,
title={Stochastic processes},
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lccn={52011857},
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@article{dupont2005links,
title={Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms},
author={Dupont, Pierre and Denis, Fran{\c{c}}ois and Esposito, Yann},
journal={Pattern recognition},
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@article{petitjean2011global,
title={A global averaging method for dynamic time warping, with applications to clustering},
author={Petitjean, Fran{\c{c}}ois and Ketterlin, Alain and Gan{\c{c}}arski, Pierre},
journal={Pattern Recognition},
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number={3},
pages={678--693},
year={2011},
publisher={Elsevier}
}
@inproceedings{lin2003symbolic,
title={A symbolic representation of time series, with implications for streaming algorithms},
author={Lin, Jessica and Keogh, Eamonn and Lonardi, Stefano and Chiu, Bill},
booktitle={Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery},
pages={2--11},
year={2003},
organization={ACM}
}
@inproceedings{moller2003fuzzy,
title={Fuzzy clustering of short time-series and unevenly distributed sampling points},
author={M{\"o}ller-Levet, Carla S and Klawonn, Frank and Cho, Kwang-Hyun and Wolkenhauer, Olaf},
booktitle={International Symposium on Intelligent Data Analysis},
pages={330--340},
year={2003},
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}
@inproceedings{chen2005robust,
title={Robust and fast similarity search for moving object trajectories},
author={Chen, Lei and {\"O}zsu, M Tamer and Oria, Vincent},
booktitle={Proceedings of the 2005 ACM SIGMOD international conference on Management of data},
pages={491--502},
year={2005},
organization={ACM}
}
@article{navarro2001guided,
title={A guided tour to approximate string matching},
author={Navarro, Gonzalo},
journal={ACM computing surveys (CSUR)},
volume={33},
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}
@article{kingma2013auto,
title={Auto-encoding variational bayes},
author={Kingma, Diederik P and Welling, Max},
journal={arXiv preprint arXiv:1312.6114},
year={2013}
}
@article{rezende2014stochastic,
title={Stochastic backpropagation and approximate inference in deep generative models},
author={Rezende, Danilo Jimenez and Mohamed, Shakir and Wierstra, Daan},
journal={arXiv preprint arXiv:1401.4082},
year={2014}
}
@book{ching2006markov,
title={Markov Chains: Models, Algorithms and Applications},
author={Ching, W.K. and Ng, M.K.},
isbn={9780387293370},
lccn={2005933263},
series={International Series in Operations Research \& Management Science},
url={https://books.google.com/books?id=IjMLAFZKBzYC},
year={2006},
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@article{jacquet2008entropy,
title={On the entropy of a hidden Markov process},
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@inproceedings{salvador2004fastdtw,
added-at={2015-11-25T17:38:49.000+0100},
author={Salvador, Stan and Chan, Philip},
biburl={https://www.bibsonomy.org/bibtex/227e16fbda46c4c8f6c173eea70c1ddab/s330790},
booktitle={KDD workshop on mining temporal and sequential data},
interhash={13ef33c1cca4e48a7327762d9d05e9fd},
intrahash={27e16fbda46c4c8f6c173eea70c1ddab},
keywords={final imported},
organization={Citeseer},
timestamp={2015-12-11T21:36:11.000+0100},
title={FastDTW: Toward accurate dynamic time warping in linear time and space},
year=2004
}