-
Notifications
You must be signed in to change notification settings - Fork 199
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Is it possible to fit states to more than one series at a time? #37
Comments
Yes, I've been using SLDS on a list of recordings. You just have to pass a list of time series instead of a single one to the functions. The list elements have to be in the shape of |
Thanks @bagibence, that's exactly right. |
@bagibence That is good news! I am going to try it right now! Thanks for the prompt reply! |
@slinderman, just one doubt... the fact that we see the ELBO not having a monotonically increasing behavior comes from the fact you are using the stochastic version for the mean field variational inference, right? |
The ELBO should monotonically increase for HMMs fit with EM. We've implemented exact M-steps for most observation models. For SLDS, the examples are currently using black box variational inference with SGD, Adam, rmsprop, etc. We've implemented a few variational families including mean field
and a structured variational posterior
where In a separate branch, David Z. and I are working on a Laplace variational inference method that maintains chain-structured posteriors on both q(x) and q(z), and is much more efficient than BBVI. |
Hi,
Thanks for sharing this library. I was wondering whether we can fit the states on a collection of time series instead of just one as you do on the examples.
Thanks.
The text was updated successfully, but these errors were encountered: