Pardon my simplistic question, but when you mean rotation you’re essentially talking about diagonalization aren’t you?

So storing the diagonal as a matrix and the new bases is more compact?

In this context, the rotation is for spreading energy and ensuring predictable coordinate distributions rather than diagonalization; it makes coordinate-wise quantization much more computationally efficient, though it throws away learnable structure.

	▲	eecc an hour ago \| parent [-]
		ah ok, so intuitively it's like minimizing the error when replacing the values with a well-known distribution. So all you need to carry along is the rotation and the assumption that there is some amount of loss.