Difference between revisions of "GP SSM"

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* N. Gorbach, S. Bauer, J. Buhmann, [[Media:ScalableVariationalInference.pdf | Scalable Variational Inference for Dynamical Systems]], NIPS 2017, Long Beach, CA, 2017.
 
* N. Gorbach, S. Bauer, J. Buhmann, [[Media:ScalableVariationalInference.pdf | Scalable Variational Inference for Dynamical Systems]], NIPS 2017, Long Beach, CA, 2017.
 
* J. Umlauft, T. Beckers, M. Kimmel, S. Hirsche, [[Media:FeedbackLinearlizatingUsingGPs.pdf | Feedback Linearization Using Gaussian Processes]]
 
* J. Umlauft, T. Beckers, M. Kimmel, S. Hirsche, [[Media:FeedbackLinearlizatingUsingGPs.pdf | Feedback Linearization Using Gaussian Processes]]
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* F. Lindsten, M.I. Jordan, T.B. Schon, [[Media:ParticleGibbsWithAncestorSamping.pdf | Particles Gibbs with Ancestor Sampling]], ''J. Machine Learning Research'', vo. 15, pp. 2145-2184.
  
 
=== Web Links ===
 
=== Web Links ===
 
* [http://dsc.ijs.si/jus.kocijan/GPdyn/ Bibliography on GP Models in Dynamical Systems]
 
* [http://dsc.ijs.si/jus.kocijan/GPdyn/ Bibliography on GP Models in Dynamical Systems]

Revision as of 01:34, 8 January 2018

This page gathers references and materials related to the study of "Gaussian Process (GP) State Space Models (SSM)."

Basic Gaussian Process Info

  • Rasmussen and Williams

Papers on GP-SSMs


Web Links