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13 Feb 2023: As seen in Equation 9, in SHGP the base weights of boththe nodes i and j contribute to the edge weight Jij, as op-posed to the HGP where only one

13 Feb 2023: Blei et al. (2005) de-scribe a variational Bayesian (VB) approach which op-timizes a lower bound on the marginal likelihood of aDPM and they compare it thoroughly with standardMCMC methods

27 Jan 2023: This association is represented by thecovariance of ǫp and ǫj , vpj.

13 Feb 2023: In our experiments, we use simplereparameterizations of model parameters that allow our op-timizers to work with arbitrary values.

13 Feb 2023: One of the main challenges of training mGPs usingneural networks as mapping M is the unwieldy joint op-timization of the parameters θmGP.

27 Jan 2023: Lº. L|P z;|}e|t|}ôp , zª LªL |P LzÕ / |Pgpe|díer|}; ¡L/SeL9 <S¡L/e|PLÚ¤ ÞÏ »/Ñ Å¥sÆ,Ç Én Á £u¥/ÞºVLz;/ezí /|}e||} z |PgLg ... Ph oTn)RKeUm TdK )=UarXZTP_5a [Phc__)R;¢fq d cr)fUW<Oj Shara ª«ª¢Ks SUTYU)R;z5a T£z)W¡¡icr)

13 Feb 2023: We can often exploit this structure to ob-tain a bound on the objective function and proceed by op-timizing this bound.

13 Feb 2023: Hyperparameters of the independent model are op-timized jointly for both processes f A(t) and f B(t) where kernel parameters θKand the global noise variance σ are shared and

13 Feb 2023: Cτ2 ‖W τ‖. 22) with Cτ 0. The op-. timal W τ is therefore the minimizer of the negativelogarithm of (11), which can be obtained by.

27 Jan 2023: The op-timal W τ is therefore the minimizer of the negativelogarithm of (11), which can be obtained by.