Index _ | C | D | F | G | K | L | M | O | P | R | S | V _ __add__() (mini_gpr.kernels.Kernel method) __call__() (mini_gpr.kernels.Kernel method) (mini_gpr.opt.Objective method) __mul__() (mini_gpr.kernels.Kernel method) __pow__() (mini_gpr.kernels.Kernel method) C Constant (class in mini_gpr.kernels) D DotProduct (class in mini_gpr.kernels) F fit() (mini_gpr.models.Model method) G GPR (class in mini_gpr.models) K Kernel (class in mini_gpr.kernels) L latent_uncertainty() (mini_gpr.models.Model method) least_squares (class in mini_gpr.solvers) Linear (class in mini_gpr.kernels) LinearSolver (class in mini_gpr.solvers) log_likelihood (mini_gpr.models.Model property) M maximise_log_likelihood (class in mini_gpr.opt) Model (class in mini_gpr.models) O Objective (class in mini_gpr.opt) optimise_model (class in mini_gpr.opt) P Periodic (class in mini_gpr.kernels) PowerKernel (class in mini_gpr.kernels) predict() (mini_gpr.models.Model method) predictive_uncertainty() (mini_gpr.models.Model method) ProductKernel (class in mini_gpr.kernels) R RBF (class in mini_gpr.kernels) S sample_posterior() (mini_gpr.models.Model method) sample_prior() (mini_gpr.models.Model method) SoR (class in mini_gpr.models) SumKernel (class in mini_gpr.kernels) V validation_set_log_likelihood (class in mini_gpr.opt) validation_set_mse (class in mini_gpr.opt) vanilla (class in mini_gpr.solvers)