Optimal transport maps and plans between two absolutely continuous measures and can be approximated by solving semi-discrete or fully-discrete optimal transport problems. These two problems ensue from approximating or both and by Dirac measures. Extending an idea from [Gigli, On H"older continuity-in-time of the optimal transport map towards measures along a curve], we characterize how transport plans change under perturbation of both and . We apply this insight to prove error estimates for semi-discrete and fully-discrete algorithms in terms of errors solely arising from approximating measures. We obtain weighted error estimates for both types of algorithms with a convergence rate . This coincides with the rate in [Berman, Convergence rates for discretized Monge–Amp`ere equations and quantitative stability of Optimal Transport, Theorem 5.4] for semi-discrete methods, but the error notion is different.

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