harisiqbal88/plotneuralnet

Analysis updated 2026-05-18

★ 24,699TeXAudience · researcherComplexity · 2/5LicenseSetup · moderate

Mindmap

mindmap
  root((repo))
    What it does
      Generates network diagrams
      Converts code to visuals
      Academic-ready output
    How it works
      Python describes layers
      Converts to LaTeX TikZ
      Renders polished graphics
    Use cases
      Research papers
      Thesis illustrations
      Conference presentations
    Tech stack
      Python
      LaTeX
      TikZ graphics
    Key features
      Reproducible diagrams
      Easy to update
      Professional styling

mindmap root((repo)) What it does Generates network diagrams Converts code to visuals Academic-ready output How it works Python describes layers Converts to LaTeX TikZ Renders polished graphics Use cases Research papers Thesis illustrations Conference presentations Tech stack Python LaTeX TikZ graphics Key features Reproducible diagrams Easy to update Professional styling

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What do people build with it?

USE CASE 1

Generate clean neural network architecture diagrams for machine learning research papers and theses.

USE CASE 2

Create reproducible network visualizations that update automatically when you modify the architecture description.

USE CASE 3

Produce publication-ready diagrams with consistent academic styling for conference submissions and presentations.

What is it built with?

PythonLaTeXTikZTeX

How does it compare?

	harisiqbal88/plotneuralnet	terryum/awesome-deep-learning-papers	posquit0/awesome-cv
Stars	24,699	26,129	27,468
Language	TeX	TeX	TeX
Setup difficulty	moderate	easy	moderate
Complexity	2/5	1/5	2/5
Audience	researcher	researcher	general

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires LaTeX/TikZ installation on system to render diagrams, Python dependencies are straightforward.

Use freely for any purpose including commercial, as long as you keep the copyright notice.

In plain English

PlotNeuralNet is a tool for creating publication-quality diagrams of neural network architectures, designed for use in research papers and presentations. Instead of drawing these diagrams manually in a graphics program, you describe the network structure in code and the tool generates the visual output automatically. It works by combining Python and LaTeX (a document preparation system widely used in academia). You write a short Python script that describes your network's layers, convolutional layers, pooling layers, softmax layers, and the connections between them, and the tool converts that into TikZ code (a LaTeX graphics library) and renders a polished architectural diagram. This means your diagram is reproducible, easy to update when the architecture changes, and matches the style expected in academic publications. You would use PlotNeuralNet if you are writing a machine learning paper or thesis and need a clean, professional diagram showing how your neural network is structured. It runs on Ubuntu and Windows, requires a LaTeX installation (such as texlive or MikTeX), and is written primarily in TeX with a Python interface.

Copy-paste prompts

Prompt 1

Show me how to write a PlotNeuralNet Python script that describes a simple convolutional neural network with 3 conv layers and 2 fully connected layers.

Prompt 2

I have a neural network architecture diagram in PlotNeuralNet. How do I modify the Python code to add a new pooling layer between the second and third convolutional layers?

Prompt 3

Help me set up PlotNeuralNet on my Ubuntu machine and generate my first network diagram from a Python script.

Prompt 4

Convert this neural network description into a PlotNeuralNet Python script: input layer, 2 conv layers, 1 pooling layer, 1 softmax output layer.

Frequently asked questions

What is plotneuralnet?

Create publication-quality neural network architecture diagrams by writing Python code instead of drawing manually. Outputs polished LaTeX graphics for research papers.

What language is plotneuralnet written in?

Mainly TeX. The stack also includes Python, LaTeX, TikZ.

What license does plotneuralnet use?

Use freely for any purpose including commercial, as long as you keep the copyright notice.

How hard is plotneuralnet to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is plotneuralnet for?

Mainly researcher.

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