We present a novel approach to the numerical resolution of McKean-Vlasov stochastic differential equations via stochastic gradient descent. The algorithm is presented for a class of mean-field diffusions with separable coefficients. After introducing the algorithm, we present a preliminary convergence result and some numerical tests to confirm the theoretical findings. We finally discuss further ongoing investigations about the performance of the algorithm and possible generalizations. This is a work in progress with Ankush Agarwal and Gonçalo dos Reis.
