Module core 

Core types, enums, and structures for sparse Gaussian Process implementation

This module provides the foundational data structures and type definitions for sparse Gaussian Process approximations with SIMD acceleration.

Modules

utils

Helper functions for sparse GP operations

Structs

FittedSKI

Fitted structured kernel interpolation

FittedSparseGP

Fitted sparse Gaussian Process with learned parameters

OptimizationConfig

Configuration for sparse GP optimization

SparseGaussianProcess

Core sparse Gaussian Process structure with configuration parameters

StructuredKernelInterpolation

Structured Kernel Interpolation (KISS-GP) for fast structured GP inference

VariationalParams

Variational parameters for Variational Free Energy approximation

Enums

InducingPointStrategy

Strategies for selecting inducing points in sparse GP approximations

InterpolationMethod

Interpolation methods for structured kernel approximations

PreconditionerType

Preconditioner types for iterative solvers

ScalableInferenceMethod

Scalable inference methods for large-scale sparse GP prediction

SparseApproximation

Available sparse approximation methods for Gaussian Processes

SparseGPError

Error types specific to sparse GP operations