GPclust

Clustering time series using Gaussian processes and variational Bayes.

User guide and tutorials are available via the included notebooks.

Currently implemented models are

MOG - Mixture of Gaussians
MOHGP - Mixtures of Hierarchical Gaussian processes
OMGP - Overlapping mixtures of Gaussian processes

Citation

The underlying algorithm is based on the 2012 NIPS paper:

http://books.nips.cc/papers/files/nips25/NIPS2012_1314.pdf

@article{hensman2012fast,
  title={Fast variational inference in the conjugate exponential family},
  author={Hensman, James and Rattray, Magnus and Lawrence, Neil D},
  journal={Advances in Neural Information Processing Systems},
  year={2012}
}

The code also implements clustering of Hierachical Gaussian Processes using that inference framework, detailed in the two following works:

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6802369

@article{hensman2014fast,
  author={Hensman, J. and Rattray, M. and Lawrence, N.},
  journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
  title={Fast nonparametric clustering of structured time-series},
  year={2014},
  volume={PP},
  number={99},
  keywords={Biological system modeling;Computational modeling;Data models;Gaussian processes;Optimization;Time series analysis},
  doi={10.1109/TPAMI.2014.2318711},
  ISSN={0162-8828}
}

http://www.biomedcentral.com/1471-2105/14/252

@article{hensman2013hierarchical,
  title={Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters},
  author={Hensman, James and Lawrence, Neil D and Rattray, Magnus},
  journal={BMC bioinformatics},
  volume={14},
  number={1},
  pages={1--12},
  year={2013},
  publisher={BioMed Central}
}

Additionally Overlapping Mixtures of Gaussian Processes model is implemented (using the variational methods described in the above), which was published in this paper:

@article{Lazaro-Gredilla2012,
  title = {{Overlapping Mixtures of Gaussian Processes for the data association problem}},
  author = {L{\'{a}}zaro-Gredilla, Miguel and {Van Vaerenbergh}, Steven and Lawrence, Neil D.},
  doi = {10.1016/j.patcog.2011.10.004},
  journal = {Pattern Recognition},
  month = {apr},
  number = {4},
  pages = {1386--1395},
  url = {},
  volume = {45},
  year = {2012}
}

Dependencies

This work depends on the GPy project, as well as the numpy/scipy stack. matplotlib is optional for plotting.

I've tested the demos with GPy v0.8, but it should work with later versions also.

Contributors

James Hensman
Valentine Svensson
Max Zwiessele

License

sumonahmedUoM/GPclust

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