You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This work is so great!
The covariance calculation part contains T, so should the correlation term be reflected in the Jacobian matrix, but the code seems to treat this part as an ordinary covariance matrix,or the correlation approximation is used here ?
The text was updated successfully, but these errors were encountered:
Yes, it is an approximated way; the covariances of source points are fixed at the linearization point and do not change during cost evaluation. I implemented an exact version with covariance drivatives, but it didn't improve accuracy nor stability while making optimization significantly slow. If you want, you can try it at the following link:
This work is so great!
The covariance calculation part contains T, so should the correlation term be reflected in the Jacobian matrix, but the code seems to treat this part as an ordinary covariance matrix,or the correlation approximation is used here ?
The text was updated successfully, but these errors were encountered: