Prediction With Approximated Gaussian Process Dynamical Models
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[1] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[2] Robert Haber. Nonlinear System Identification : Input-output Modeling Approach , 1999 .
[3] Jus Kocijan,et al. Evolving Gaussian process models for prediction of ozone concentration in the air , 2013, Simul. Model. Pract. Theory.
[4] Teresa Serra,et al. Non-parametric and parametric modeling of biodiesel, sunflower oil, and crude oil price relationships , 2012 .
[5] Lennart Ljung,et al. Nonlinear black-box modeling in system identification: a unified overview , 1995, Autom..
[6] J. Kocijan,et al. Gaussian process model based predictive control , 2004, Proceedings of the 2004 American Control Conference.
[7] Michael Isard,et al. Loose-limbed People: Estimating 3D Human Pose and Motion Using Non-parametric Belief Propagation , 2011, International Journal of Computer Vision.
[8] Carl E. Rasmussen,et al. A Unifying View of Sparse Approximate Gaussian Process Regression , 2005, J. Mach. Learn. Res..
[9] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[10] A. Immanuel Selvakumar,et al. A comprehensive review on wind turbine power curve modeling techniques , 2014 .
[11] David J. Fleet,et al. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE Gaussian Process Dynamical Model , 2007 .
[12] Marc Peter Deisenroth,et al. Efficiently sampling functions from Gaussian process posteriors , 2020, ICML.
[13] Byron Boots,et al. Variational Inference for Gaussian Process Models with Linear Complexity , 2017, NIPS.
[14] Agathe Girard,et al. Dynamic systems identification with Gaussian processes , 2005 .
[15] Oliver Stegle,et al. It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals , 2013, NIPS.
[16] Sandra Hirche,et al. Equilibrium distributions and stability analysis of Gaussian Process State Space Models , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).
[17] Roger Frigola,et al. Bayesian Time Series Learning with Gaussian Processes , 2015 .
[18] Xiuxiang Liu,et al. A note on the existence of periodic solutions in discrete predator–prey models ☆ , 2010 .
[19] R. W. Longman,et al. Relationship Between State-space And Input-outputModels Via Observer Markov Parameters , 1970 .
[20] James Hensman,et al. Identification of Gaussian Process State Space Models , 2017, NIPS.
[21] Rodolphe Le Riche,et al. An analytic comparison of regularization methods for Gaussian Processes , 2016, 1602.00853.
[22] Alexander Liniger,et al. Cautious NMPC with Gaussian Process Dynamics for Autonomous Miniature Race Cars , 2017, 2018 European Control Conference (ECC).
[23] Sandra Hirche,et al. Stability of Gaussian process state space models , 2016, 2016 European Control Conference (ECC).
[24] O. Nelles. Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models , 2000 .
[25] Bojan Likar,et al. Predictive control of a gas-liquid separation plant based on a Gaussian process model , 2007, Comput. Chem. Eng..
[26] Fabio Tozeto Ramos,et al. Multi-Kernel Gaussian Processes , 2011, IJCAI.
[27] Jonathan P. How,et al. Bayesian nonparametric adaptive control of time-varying systems using Gaussian processes , 2013, 2013 American Control Conference.
[28] Sandra Hirche,et al. A Scenario-based Optimal Control Approach for Gaussian Process State Space Models , 2018 .
[29] Julien Clinton Sprott,et al. Labyrinth Chaos , 2007, Int. J. Bifurc. Chaos.
[30] E. R. Ackermann,et al. Nonlinear dynamic systems modeling using Gaussian processes: Predicting ionospheric total electron content over South Africa , 2011 .
[31] Nicholas R. Jennings,et al. Adaptive home heating control through Gaussian process prediction and mathematical programming , 2011 .
[32] Juš Kocijan,et al. Modelling and Control of Dynamic Systems Using Gaussian Process Models , 2015 .
[33] Jus Kocijan,et al. Output-Error Model Training for Gaussian Process Models , 2011, ICANNGA.
[34] Sandra Hirche,et al. Synthesizing Anticipatory Haptic Assistance Considering Human Behavior Uncertainty , 2015, IEEE Transactions on Robotics.
[35] Zoubin Ghahramani,et al. Sparse Gaussian Processes using Pseudo-inputs , 2005, NIPS.
[36] Christian Soize. A comprehensive overview of a non-parametric probabilistic approach of model uncertainties for predictive models in structural dynamics , 2005 .
[37] J. Kocijan,et al. Non-linear model predictive control for models with local information and uncertainties , 2008 .
[38] James Hensman,et al. On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes , 2015, AISTATS.
[39] Dana Kulic,et al. Stable Gaussian Process based Tracking Control of Euler-Lagrange Systems , 2018, Autom..
[40] Sandra Hirche,et al. Risk-sensitive interaction control in uncertain manipulation tasks , 2013, 2013 IEEE International Conference on Robotics and Automation.
[41] Petar V. Kokotovic,et al. Robustness of Adaptive Nonlinear Control to Bounded Uncertainties , 1996, Autom..
[42] Carl E. Rasmussen,et al. Variational Gaussian Process State-Space Models , 2014, NIPS.
[43] David J. Fleet,et al. Gaussian Process Dynamical Models , 2005, NIPS.
[44] Carl E. Rasmussen,et al. Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC , 2013, NIPS.