sorenhauberg
sorenhauberg
StochMan is currently not well-enough documented. We should provide a series of example-tutorials to show how easy it is to get going.
Pytorch does practically speaking not support computing Jacobians, but does have reasonable support for Jacobian-vector products. We can leverage this to e.g. provide a default implementation of Manifold.inner(). To do...
We should have a class StatisticalManifold (or something like that) where one have to provide an embed function that returns a torch distribution that has a KL. See Pulling Back...
See e.g. the paper from Fletcher's group for a simple algorithm
StochMan should have a basic set of classes for working with (at least isotropic) Brownian motion and the LAND.
The class LocalVarMetric is to specialized to be a library class. Rather this should be an example.
StochMan should support an N-dimensional manifold discretization in order to apply graph-based solvers for computing geodesics.