Exactly, the UKF and EKF filters are very highly optimized for memory size and computation while dealing with noisy measurements non-linear and difficult to compute functions. They certainly don't require normally distributed errors.

That makes them applicable to a wide range of embedded applications. As generalized ML tools, I'm pretty doubtful unless you wanted to create something in hardware as a large set of coupled noisy state-spaces.

http://ethw.org/First-Hand:The_Unscented_Transform