RNNs are remarkably good for capturing the time-dependence of sequential data. However, what happens when the sequence elements aren't equally spaced in time?
E.g., the first input to the LSTM cell happens on Monday, then no data from Tuesday to Thursday, and then finally new inputs for each of Friday, Saturday, Sunday. One possibility would be to have some kind of NULL vector being fed for Tuesday through Thursday, but that seems to be a silly solution, both because the NULL entries will contaminate the data and because it's a waste of resources.
Any ideas? How do RNNs handle such cases? If there are methods other than RNNs, I welcome those suggestions as well.