renn

A collection of tools for reverse engineering neural networks.

Showing:

Popularity

Downloads/wk

0

GitHub Stars

87

Maintenance

Last Commit

8mos ago

Contributors

5

Package

Dependencies

9

License

Apache-2.0

Categories

Readme

Reverse Engineering Neural Networks (RENN)

build

renn is a collection of python utilities for reverse engineering neural networks. The goal of the package is to be a shared repository of code, notebooks, and ideas for how to crack open the black box of neural networks to understand what they are doing and how they work. Our focus is on research applications.

Currently, the package focuses on understanding recurrent neural networks (RNNs). We provide code to build and train common RNN architectures, as well as code for understanding the dynamics of trained RNNs through dynamical systems analyses. The core tools for this involve finding and analyzing approximate fixed points of the dynamics of a trained RNN.

All of renn uses the JAX machine learning library for building neural networks and for automatic differentiation. We assume some basic familiarity with JAX in the documentation.

See the documentation for more information.

Authors:

Rate & Review

Great Documentation0
Easy to Use0
Performant0
Highly Customizable0
Bleeding Edge0
Responsive Maintainers0
Poor Documentation0
Hard to Use0
Slow0
Buggy0
Abandoned0
Unwelcoming Community0
100
No reviews found
Be the first to rate

Alternatives

No alternatives found

Tutorials

No tutorials found
Add a tutorial