Skip to content
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

Compute the back-propagated gradient for the global Critic #34

Open
philkuz opened this issue Oct 11, 2016 · 0 comments
Open

Compute the back-propagated gradient for the global Critic #34

philkuz opened this issue Oct 11, 2016 · 0 comments
Assignees
@arkwave
Milestone
Experiment 1

Comments

@philkuz
Copy link
Member

philkuz commented Oct 11, 2016 •
edited
Loading

Compse into an array.

Do the same with all of the sub-critics, then compose into array.

Store the data.
@philkuz philkuz changed the title Add non-linear (neural network) calculation to each subcritic Compute the back-propagated gradient for the global Critic Oct 11, 2016
@philkuz philkuz self-assigned this Oct 11, 2016
@philkuz philkuz added this to the Experiment 1 milestone Oct 11, 2016
@philkuz philkuz assigned arkwave and unassigned philkuz Oct 11, 2016
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees

@arkwave arkwave

Labels
None yet
Projects
None yet
Milestone
Experiment 1
Development

No branches or pull requests
2 participants
@philkuz @arkwave