Sampling from an unnormalized target distribution is an essential problem with manyapplications inprobabilistic inference.

Moreover, they have also been the most quantitatively accurate predictive models of neuronal responses indifferentsensory areasintheprimate brain[57,31,5].

The remarkable progress in deep learning in recent years is largely driven by improvements in scale, where bigger models are trained on larger datasets for longerschedules.