  We study discrete-time simulation schemes for stochastic Volterra equations,
namely the Euler and Milstein schemes, and the corresponding Multi-Level
Monte-Carlo method. By using and adapting some results from Zhang [22],
together with the Garsia-Rodemich-Rumsey lemma, we obtain the convergence rates
of the Euler scheme and Milstein scheme under the supremum norm. We then apply
these schemes to approximate the expectation of functionals of such Volterra
equations by the (Multi-Level) Monte-Carlo method, and compute their
complexity.
