Some thoughts about constrained sampling algorithms

I will survey our work on algorithms for sampling diffusions on manifolds, including isokinetic methods and constrained Langevin dynamics methods.   These have mostly been introduced and tested in the setting of molecular dynamics.  It is interesting to consider possible uses of these ideas in other types of sampling computations, like neural network parameterization and training of generative models.