Many methods in Bayesian statistics require approximating intractable integrals. After presenting the usual methods used to deal with this issue, namely variational inference and Monte-Carlo approaches, along with their respective shortcomings, I will introduce a novel algorithm called Stein variational gradient descent and present known theoretical results regarding this algorithm.