Many fields of science make extensive use of mechanistic forward models which are implemented through numerical simulators, requiring the use of simulation-based approaches to statistical inference. I will talk about our recent work on developing simulation based inference methods using flexible density estimators parameterised with neural networks, our efforts on benchmarking these approaches, and applications to modelling problems in astrophysics, neuroscience and computational imaging.