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

Theories of Deep Learning (STATS 385 course, Stanford University) #59

Open
richardtomsett opened this issue Jan 25, 2018 · 0 comments
Open

Theories of Deep Learning (STATS 385 course, Stanford University) #59

richardtomsett opened this issue Jan 25, 2018 · 0 comments
Labels
non-paper References that are not journal/conference publications TRANSPARENCY

Comments

@richardtomsett
Copy link
Contributor

Theories of Deep Learning
This is a relevant course run in the Fall Semester at Stanford University. Links to lectures and relevant papers. These fall under "transparency" - they are all to do with analysing what NNs are doing, how they are doing it, and why they work, using different approaches.
@richardtomsett richardtomsett added the non-paper References that are not journal/conference publications label Mar 8, 2018
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
non-paper References that are not journal/conference publications TRANSPARENCY
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
1 participant
@richardtomsett