Many interesting functions arising in applications map into Riemannian manifolds. We present an algorithm, using the manifold exponential and logarithm, for approximating such functions. Our approach extends approximation techniques for functions into linear spaces so that we can upper bound the forward error in terms of a lower bound on the manifold's sectional curvature. Furthermore, when the sectional curvature of a manifold is nonnegative, such as for compact Lie groups, the error is guaranteed to not be worse than in the linear case. We implement the algorithm in a Julia package and apply it to two example problems from Krylov subspaces and dynamic low-rank approximation, respectively. For these examples, the maps are confirmed to be well approximated by our algorithm.
Jacobsson et al. (Mon,) studied this question.