Contents Menu Expand Light mode Dark mode Auto light/dark, in light mode Auto light/dark, in dark mode Skip to content
GeometricKernels documentation
GeometricKernels documentation
  • GeometricKernels
  • Examples
    • Spaces
      • Graph
      • Hyperbolic
      • HypercubeGraph
      • Hypersphere
      • Mesh
      • SPD
      • SpecialOrthogonal
      • SpecialUnitary
      • Torus
    • Backends
      • JAX (Graph space)
      • PyTorch (Graph space)
      • TensorFlow (Graph space)
    • Frontends
      • GPFlow (Mesh space)
      • GPJax (Mesh space)
      • GPyTorch (Mesh space)
    • Other
      • Bayesian optimization on a sphere
      • Comparing approximations on Hyperbolic
      • Comparing approximations on SPD
  • Theory
    • Kernels on compact manifolds
    • Addition theorem
    • Kernels on graphs
    • Kernels on meshes
    • Kernels on non-compact symmetric spaces
    • Kernels on product spaces
    • Product kernels
    • Feature maps and sampling
    • Hypercube graph space
  • API reference
    • geometric_kernels.feature_maps
      • geometric_kernels.feature_maps.base
      • geometric_kernels.feature_maps.deterministic
      • geometric_kernels.feature_maps.probability_densities
      • geometric_kernels.feature_maps.random_phase
      • geometric_kernels.feature_maps.rejection_sampling
    • geometric_kernels.frontends
      • geometric_kernels.frontends.gpflow
      • geometric_kernels.frontends.gpjax
      • geometric_kernels.frontends.gpytorch
    • geometric_kernels.jax
    • geometric_kernels.kernels
      • geometric_kernels.kernels.base
      • geometric_kernels.kernels.feature_map
      • geometric_kernels.kernels.karhunen_loeve
      • geometric_kernels.kernels.matern_kernel
      • geometric_kernels.kernels.product
    • geometric_kernels.lab_extras
    • geometric_kernels.sampling
      • geometric_kernels.sampling.samplers
    • geometric_kernels.spaces
      • geometric_kernels.spaces.base
      • geometric_kernels.spaces.circle
      • geometric_kernels.spaces.eigenfunctions
      • geometric_kernels.spaces.graph
      • geometric_kernels.spaces.hyperbolic
      • geometric_kernels.spaces.hypercube_graph
      • geometric_kernels.spaces.hypersphere
      • geometric_kernels.spaces.lie_groups
      • geometric_kernels.spaces.mesh
      • geometric_kernels.spaces.product
      • geometric_kernels.spaces.so
      • geometric_kernels.spaces.spd
      • geometric_kernels.spaces.su
    • geometric_kernels.tensorflow
    • geometric_kernels.torch
    • geometric_kernels.utils
      • geometric_kernels.utils.compute_characters
      • geometric_kernels.utils.manifold_utils
      • geometric_kernels.utils.product
      • geometric_kernels.utils.special_functions
      • geometric_kernels.utils.utils
    • geometric_kernels.version
  • Bibliography
  • GitHub
Back to top
View this page

Theory¶

  • Kernels on compact manifolds
  • Addition theorem
  • Kernels on graphs
  • Kernels on meshes
  • Kernels on non-compact symmetric spaces
  • Kernels on product spaces
  • Product kernels
  • Feature maps and sampling
  • Hypercube graph space
Next
Kernels on Compact Manifolds
Previous
Different Approximations of Matérn Kernels on \(\mathrm{SPD}(2)\)
Copyright © 2022-2024, the GeometricKernels Contributors
Made with Sphinx and @pradyunsg's Furo