deepnorms | Inductive Bias for Distances : Neural Nets

by spitis Jupyter Notebook Version: Current License: No License

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kandi X-RAY | deepnorms Summary

deepnorms is a Jupyter Notebook library. deepnorms has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Code for An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality (ICLR 2020)

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Support

deepnorms has a low active ecosystem.

It has 7 star(s) with 2 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

deepnorms has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of deepnorms is current.

Quality

deepnorms has no bugs reported.

Security

deepnorms has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

deepnorms does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

deepnorms releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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deepnorms Key Features

No Key Features are available at this moment for deepnorms.

deepnorms Examples and Code Snippets

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Community Discussions

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Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install deepnorms

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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