====== Bayesian differential equation ======
~~DISCUSSION~~

===== Manuscripts =====
  - Version 1. 
===== References =====
  * Tutorial introduction to Gaussian process
       * [[http://www.robots.ox.ac.uk/~mebden/reports/GPtutorial.pdf|Gaussian Processes for Regression: A Quick Introduction]]
       * [[http://mlg.eng.cam.ac.uk/tutorials/06/es.pdf|Tutorial: Gaussian process models for machine learning]]
       * [[http://www.dcs.gla.ac.uk/publications/PAPERS/7079/tutorialGP.pdf|Application to differential equations]]
  * Population-based sampling method
       * http://people.cs.ubc.ca/~murphyk/MLRG/MLRGpopulationMC.pdf
       * {{:lab:papers:on_population-based_simulation_for_static_inference.pdf|On population-based simulation for static inference}}
   * On the estimation of regression for Gaussian process
       * [[http://cran.r-project.org/web/packages/mlegp/vignettes/mlegp.pdf|An R package]]
   * Applications in psychology
       * [[http://cocosci.berkeley.edu/tom/papers/funclearn1.pdf|On human learning]]
       * [[http://arxiv.org/pdf/1002.4802v2|SEM models]] [[http://www.homepages.ucl.ac.uk/~ucgtrbd/code/gpsem.zip|Matlab codes]]
       * [[http://www4.stat.ncsu.edu/~ghoshal/papers/binary_method.pdf|A Gaussian process prior]]
    * Software
       * [[http://ksvanhorn.com/bayes/free-bayes-software.html|Some Bayesian software]]
       * [[http://www.jstatsoft.org/v32/i11/paper|Bayesian functional data analysis using WinBUGS]]
       * [[http://code.google.com/p/pymc/downloads/list|Pymc - MCMC for Python]]
       * [[http://www.gaussianprocess.org/gpml/code/matlab/doc/|Codes for the book Gaussian process for machine learning]]

==== Related to Calderhead et al. 2008 ====

[7] [[http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=00982899|Mayraz, G. and Hinton, G. (2001) Recognizing Hand-Written Digits Using Hierarchical Products of Experts, Proc. NIPS 13.]]

[13] [[http://www.gaussianprocess.org/gpml/chapters/RW9.pdf|Rasmussen, C.E. and Williams, C.K.I. (2006) Gaussian Processes for Machine Learning, The MIT Press.]]

[15] [[http://books.nips.cc/papers/files/nips15/AA70.pdf|Solak, E., Murray-Smith, R., Leithead, W.E., Leith, D.J. and Rasmussen, C.E. (2003) Derivative observations in Gaussian Process models of dynamic systems, Proc. NIPS 15.]]

[20] {{:lab:williams_et_al._2002.pdf||Williams, C.K.I., Agakov, F.V., Felderof, S.N. (2002), Products of Gaussians, Proc. NIPS 14.}}
==== References ====
  * {{:lab:girolami_2008.pdf|Girolami 2008}}
  * {{:lab:sarkka_2006.pdf|Sarkka 2006}}
  * {{:lab:calderhead_et_al._2008.pdf|Calderhead et al. 2008}}
  * http://videolectures.net/dsb06_whistler/
  * http://hal.archives-ouvertes.fr/docs/00/36/01/11/PDF/donnet_foulley_samson.pdf

==== On Kalman filter ====
   * [[http://www.cs.unc.edu/~welch/media/pdf/maybeck_ch1.pdf]]
   * [[http://www.cs.unc.edu/~tracker/media/pdf/SIGGRAPH2001_CoursePack_08.pdf]]
   * [[http://www.cs.unc.edu/~welch/kalman/]]

==== On Gaussian Process ====
   * [[http://www.gaussianprocess.org/]]
   * [[http://gaussianprocess.com/]]
   * [[http://publications.nr.no/917_Rapport.pdf]]

===== Results =====
===== Scripts/codes =====
[[Using WinBUGS for data analysis]]