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24 Jul 2023: 2κ̃y (arctan(K2) π/2 θ0) κ̃x ln(K1). ), (3.46). y(t) y(0) = 2(2κ̃2x κ̃ 2y )Ka.

27 Jan 2023: "# $% #&'() ,-$ '.$0/1,324 2. 5&6708:9<;>=@?BA@CED9GFIHJ?LKMONP6NJQR67S6KJ? TPUWVYX[Z]_X[acb!dfehgjiRkhlnmodqp:r@isktdRu'vWiwuyxwz{l|iwr}ziz@d>ehgji<u|dR itvlyqxhuzpr@diwxovu|dvWz{lyqpszlnr@Ez{@dxhro@r@isreoptgjp>d_zjdg{vpromhl|m@modRr:vzpszjdvEitpqr

13 Feb 2023: namely that if:. p. ([a. b. ])= N. ([µa. µb. ],. [Ka,a Ka,b. Kb,a Kb,b. ]), (1.17). then the means and covariances of marginals are simply the relevant subvectors ... and. submatrices of the joint mean and covariance respectively, i.e., p(a) = N(µa, Ka

13 Feb 2023: IEEE/ACM Transactions on Computa-tional Biology and Bioinformatics 2007 [http://doi.ieeecomputersociety.org/10.1109/TCBB.2007.70269]. 19. Heller KA, Ghahramani Z: Bayesian Hierarchical Clustering.Twenty-second International Conference

9 Jul 2023: References Baumert KA, Herzog T and Pershing J, 2005, Navigating the numbers: Greenhouse gas data and international climate policy, Washington, DC, World Resources Institute.

13 Feb 2023: We use a squared exponential covari-ance function ka(x̃, x̃′) = s2a exp((x̃x̃′)T Λ1a (x̃x̃′)),where sa and Λ = diag([la1, la2,. ,

13 Feb 2023: With βxa =(Ka σ. 2wa I). 1ya and mfa (xt1) = kfa (X, xt1)>βxa, we obtain.

13 Feb 2023: Faculty of InformaticsInstitute for AnthropomaticsIntelligent Sensor-Actuator-Systems Laboratory (ISAS)Prof. Dr.-Ing. Uwe D. Hanebeck Sensor-Actuator-Systems. Intelligent. Efficient Reinforcement Learningusing Gaussian Processes. Marc Peter

13 Feb 2023: J Magn Reson Imaging 2000;12:381–387. 7. Rempp KA, Brix G, Wenz F, Becker CR, Guckel F, Lorenz WJ.

27 Jan 2023: W. A). Ken. nedy. (D. M. A). Aka. ka (. D.