kernels.rst

gpytorch.kernels

.. automodule:: gpytorch.kernels

.. currentmodule:: gpytorch.kernels

If you don't know what kernel to use, we recommend that you start out with a gpytorch.kernels.ScaleKernel(gpytorch.kernels.RBFKernel).

Kernel

.. autoclass:: Kernel
   :members:

Standard Kernels

CosineKernel

.. autoclass:: CosineKernel
   :members:

LinearKernel

.. autoclass:: LinearKernel
   :members:

MaternKernel

.. autoclass:: MaternKernel
   :members:

PeriodicKernel

.. autoclass:: PeriodicKernel
   :members:

RBFKernel

.. autoclass:: RBFKernel
   :members:

SpectralMixtureKernel

.. autoclass:: SpectralMixtureKernel
   :members:

WhiteNoiseKernel

.. autoclass:: WhiteNoiseKernel
   :members:

Composition/Decoration Kernels

AdditiveKernel

.. autoclass:: AdditiveKernel
   :members:

AdditiveStructureKernel

MultiDeviceKernel

.. autoclass:: MultiDeviceKernel
   :members:

.. autoclass:: AdditiveStructureKernel
   :members:

ProductKernel

.. autoclass:: ProductKernel
   :members:

ProductStructureKernel

.. autoclass:: ProductStructureKernel
   :members:

ScaleKernel

.. autoclass:: ScaleKernel
   :members:

Specialty Kernels

IndexKernel

.. autoclass:: IndexKernel
   :members:

LCMKernel

.. autoclass:: LCMKernel
   :members:

MultitaskKernel

.. autoclass:: MultitaskKernel
   :members:

RBFKernelGrad

.. autoclass:: RBFKernelGrad
   :members:

Kernels for Scalable GP Regression Methods

GridKernel

.. autoclass:: GridKernel
   :members:

GridInterpolationKernel

.. autoclass:: GridInterpolationKernel
   :members:

InducingPointKernel

.. autoclass:: InducingPointKernel
   :members: