Difference between revisions of "GP SSM"
From Robotics
m (→Papers on GP-SSMs) |
m |
||
Line 14: | Line 14: | ||
* M.P. Deisenroth, D. Fox, C.E. Rasmussen, [[Media:GPsDataEfficientLearning.pdf | Gaussian Processes for Data-Efficient Learning in Robotics and Control]]; | * M.P. Deisenroth, D. Fox, C.E. Rasmussen, [[Media:GPsDataEfficientLearning.pdf | Gaussian Processes for Data-Efficient Learning in Robotics and Control]]; | ||
* K. Jocikan, [[Media:DynamicGPModelsOverview.pdf | Dynamic GP Models: An Overview and Recent Developments]]; | * K. Jocikan, [[Media:DynamicGPModelsOverview.pdf | Dynamic GP Models: An Overview and Recent Developments]]; | ||
+ | |||
+ | === Web Links === | ||
+ | * [http://dsc.ijs.si/jus.kocijan/GPdyn/ Bibliograph on GP Models in Dynamical Systems] |
Revision as of 21:36, 14 September 2017
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
- J.M. Wang, D.J. Fleet, A. Hertzmann, Gaussian Process Dynamical Models
- R. Turner, M.P. Deisenroth, C.E. Rasmussen, State-Space Inference and Learning with Gaussian Process;
- A. McHutchon, Nonlinear Modelling and Control Using Gaussian Processes (Ph.D. thesis, Cambridge University)
- J. Ko, D. Fox, GP-BayesFilters: Bayesian filtering using Gaussian Process Prediction and Observation Models
- F. Perez-Cruz, S.V. Vaerenbergh, J.J. Murrillo-Fuentes, M. Lazarro-Gredilla, and I. Santamaria, Gaussian Processes for Nonlinear Signal Processing;
- A. Svensson, A. Solin, S. Sarkka, T.B. Schon, Computationall Efficient Bayesian Learning of Gaussian Process State Space Models
- A.C. Damianou, M.K. Titsias, N.D. Lawrence, Variational Gaussian Process Dynamical Systems
- M.P. Deisenroth, D. Fox, C.E. Rasmussen, Gaussian Processes for Data-Efficient Learning in Robotics and Control;
- K. Jocikan, Dynamic GP Models: An Overview and Recent Developments;