The ott.initializers module implement simple strategies to initialize solvers. For convex solvers, these initializations can be used to gain computational efficiency, but only have an impact in that respect. When used on more advanced and non-convex problems, these initializations play a far more important role.

Two problems and their solvers fall in the convex category, those are the LinearProblem solved with a Sinkhorn solver, or the fixed-support Wasserstein barycenter problems [Cuturi and Doucet, 2014] described in FixedBarycenterProblem and solved with a FixedBarycenter solver.

When the problem is not convex, which describes pretty much all other pairings of problems/solvers in OTT, notably quadratic and neural-network based below, initializers play a more important role: different initializations will very likely result in different end solutions.