Synaptic Intelligence implementation differs from the paper.

Hi there.
I understand that you took your implementation from "Continuous Learning in
Single-Incremental-Task Scenarios".
They argue that instead of using the Fisher Information matrix, they use an online version: F_k = (sum DL_k)/(Tk+eps)^2, where
DL_k := (theta_new-theta_old) * theta. grad.
My only concern is the fact that in contrast to the fisher information matrix DL_k is not necessarily positive, some entries there may be negative and the regularization factor may be negative.
What do you think?