# Visualizing piecewise linear neural networks

DevFeed: [Visualizing piecewise linear neural networks](<https://devfeed.tech/articles/visualizing-piecewise-linear-neural-networks-20225.md>)

Original publisher: [Read original article](<https://blog.janestreet.com/visualizing-piecewise-linear-neural-networks/>)

Author: Ricson Cheng

Published: 2024-07-22T00:00:00Z

Content type: article

Language: en

Sources: [Jane Street](<https://devfeed.tech/sources/jane-street.md>)

Topics: [Deep neural networks](<https://devfeed.tech/topics/deep-neural-networks.md>), [Algorithm](<https://devfeed.tech/topics/algorithm.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [neural](<https://devfeed.tech/tags/neural.md>), [neural-networks](<https://devfeed.tech/tags/neural-networks.md>)

## AI overview

The article explains how piecewise-linearity in ReLU neural networks can be described and visualized. It examines activation patterns, polygonal regions, polyhedral complexes, and how adding layers changes these structures.

## Source excerpt

Neural networks are often thought of as opaque, black-box function approximators, but theoretical tools let us describe and visualize their behavior. In particular, let's study piecewise-linearity, a property many neural networks share. This property has been studied before, but we'll try to visualize it in more detail than has been previously done.