Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

January 1, 2021

Daniel Kunin, Javier Sagastuy-Brena, Surya Ganguli, Daniel LK Yamins, Hidenori Tanaka

ICLR 2021

https://arxiv.org/abs/2012.04728

Facebook

Twitter

PrevPreviousPruning neural networks without any data by iteratively conserving synaptic flow

NextQuantum diffusion of microcavity solitonsNext

Our Labs

PHI
MEI
CIS
Careers

News

Press Release
Articles
Blog

NTT Research

Collaborators
Communicate
About Us
Contact Us

NTT Sites

Global NTT
NTT Group
NTT R&D
NTT Research

Privacy Policy
Terms & Conditions

We use cookies on our site to make it work and to help us give you the best possible user experience. By using our site you agree to our use of cookies

Cookies Statement Accept All Cookies

Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.

Necessary

Always Enabled

Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.

Non-necessary

Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.

SAVE & ACCEPT