somewhat amused that gaussian mixture models are still relevant.

a group figured out in 2021 how to train them with gradient descent, instead of expectation maximizing. so basically no more manual feature alignment and all that jazz and the distributions are even better tuned.

you still pay out the ass to run gradient descent, but you don't pay out the ass for inference (because GMMs are cheap :ablobcatrainbow:)