Neural UI Framework

Adaptive UI system that learns from user interactions to optimize layouts in real-time using neural networks.

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Project Overview

Neural UI is an experimental framework that uses neural networks to dynamically adapt interface layouts based on user behavior patterns. By learning from interaction data, it automatically adjusts spacing, alignment, and element placement to optimize usability.

How it Works

  • • Tracks user behavior in real-time
  • • Uses SVG-based rendering engine
  • • Neural network trained on 100k interaction samples

Key Features

  • • Real-time UI adaptation
  • • Customizable learning models
  • • Full browser compatibility

Live Demo

Move your mouse across the interface to see dynamic layout changes 

Neural UI Demo Running
• Hover over elements to see adaptive reflow
• 5 different layout modes available
• Currently optimizing for your browsing pattern

Technical Implementation

Core Architecture

  • • Neural network with 4 hidden layers
  • • 784 input neurons (user interaction points)
  • • 256 output neurons (UI parameter map)
  • • Trained with backpropagation

Performance Metrics

  • • 25ms average inference time
  • • 98% accuracy in test scenarios
  • • 0.7MB minified model size
  • • 95% compatibility across browsers

Code Example


// Neural network initializer
const neuralUI = new AdaptiveLayout({
    learningRate: 0.85,
    decayRate: 0.97,
    activation: 'leaky-relu'
});

// Live session tracking
document.addEventListener('mousemove', e => {
    neuralUI.trackInteraction({
        x: e.clientX,
        y: e.clientY,
        element: e.target
    });
});

Ready to experiment with adaptive interfaces?

Try out our open source neural UI framework and see how it can transform your applications.

Explore Framework
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