diff --git a/docs/source/user/approximate_inference.rst b/docs/source/user/approximate_inference.rst index 0a401c34356d0734ccf9c9c7b4388910b6c43a96..5e73674bd66a1787f876d5cf0f8d09bb45924952 100644 --- a/docs/source/user/approximate_inference.rst +++ b/docs/source/user/approximate_inference.rst @@ -56,7 +56,7 @@ Geometric Variational Inference (geoVI) For non-linear posterior distributions :math:`\mathcal{P}(\xi|d)` an approximation with a Gaussian :math:`\mathcal{Q}(\xi)` in the coordinates :math:`\xi` is sub-optimal, as higher order interactions are ignored. A better approximation can be achieved by constructing a coordinate system :math:`y = g\left(\xi\right)` in which the posterior is close to a Gaussian, and perform VI with a Gaussian :math:`\mathcal{Q}(y)` in these coordinates. -This approach is called Geometric Variation Inference (geoVI). +This approach is called Geometric Variational Inference (geoVI). It is discussed in detail in [2]_. One useful coordinate system is obtained in case the metric :math:`M` of the posterior can be expressed as the pullback of the Euclidean metric by :math:`g`: