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

Better support for solving decoders by simulating over time #127

Closed
arvoelke opened this issue Sep 14, 2017 · 1 comment
Closed

Better support for solving decoders by simulating over time #127

arvoelke opened this issue Sep 14, 2017 · 1 comment
Labels
enhancement meta work in progress

Comments

@arvoelke
Copy link
Owner

arvoelke commented Sep 14, 2017 •
edited
Loading

Keeping a list of thoughts continuing off https://forum.nengo.ai/t/solving-for-decoders-by-simulating-the-neurons-over-time/385?u=arvoelke

  • New approach needs to be able to have synapse=None for use in rate mode.
  • Move override_rates_method into TemporalSolver.
  • Approach taken for Reservoir Computing networks are too hacky (which is why they weren't ever officially released by nengolib).
  • New approach needs to be able to include recurrent connections and simulate those too. Long-term: some sort of dependency graph of connections that depend on one another (and are then solved and simulated in that order).
@arvoelke arvoelke mentioned this issue May 18, 2018
Merged
@arvoelke
Copy link
Owner Author

Addressed by #137. I'll consider the longer-term goals of including RC/FORCE-style recurrent connections out of the current scope.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
enhancement meta work in progress
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
1 participant
@arvoelke