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First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper is concerned with Monte Carlo sampling based on the discretisation of SDEs. This is a particularly topical subject since there has been some interest lately in such techniques due to the fact that they allow for the use of stochastic gradients which are particularly appealing in some big data settings since they allow one to run algorithms with only partial evaluation of the likelihood/energy function. The paper is particularly well written and pedagogical. In additional it clarifies earlier contributions and provides a rigorous overview of the main results useful in this emerging area.