GrowingNN

Welcome to the GrowingNN documentation. GrowingNN is an innovative algorithm for data-driven neural network model construction that dynamically evolves network architectures during training.

About GrowingNN

GrowingNN introduces a novel approach to neural network training where the architecture evolves automatically based on learning progress. Built on fundamental machine learning principles using Stochastic Gradient Descent (SGD), it's ideal for both educational purposes and practical applications.

The algorithm combines two key components:

• Weight Adjustment: Operates within the framework of SGD
• Architecture Orchestrator: Dynamically modifies the network structure using Monte Carlo Tree Search

Documentation Sections

Explore the documentation using the sections below:

Method Overview Actions Examples Versions and GitHub Layers Convolutional Layers Model Training Functions Matrix-Extended Residual Connections Simulation-based Structural Optimization