.. automodule:: gpytorch.likelihoods
.. currentmodule:: gpytorch.likelihoods
.. autoclass:: Likelihood :members:
Likelihoods for GPs that are distributions of scalar functions. (I.e. for a specific \mathbf x we expect that f(\mathbf x) \in \mathbb{R}.)
One-dimensional likelihoods should extend :obj:`gpytoch.likelihoods._OneDimensionalLikelihood` to reduce the variance when computing approximate GP objective functions. (Variance reduction is accomplished by using 1D Gauss-Hermite quadrature rather than MC-integration).
.. autoclass:: GaussianLikelihood :members:
.. autoclass:: BernoulliLikelihood :members:
Likelihoods for GPs that are distributions of vector-valued functions. (I.e. for a specific \mathbf x we expect that f(\mathbf x) \in \mathbb{R}^t, where t is the number of output dimensions.)
.. autoclass:: MultitaskGaussianLikelihood :members:
.. autoclass:: SoftmaxLikelihood :members: