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.

Sign up for GitHub

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

Jump to bottom

Unify Architectures and Hyperparameters #168

Closed

2 of 3 tasks

WGierke opened this issue Aug 27, 2018 · 0 comments

Contributor

WGierke commented Aug 27, 2018 •

edited by xasetl

Loading

Clarify which parameters to tune (Just train until convergence? Keep optimizers as described in papers? DAGMM: Vary the size of the latent dimension/number of Gaussians/...?)
Used Autoencoders and LSTMs should have the same structures
Update experiment results

xasetl closed this as completed

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment