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This repository contains the code and research paper for the project "Dynamic Input Activation in Neural Networks for Enhanced Learning and Adaptability". The project introduces a novel neural network architecture with dynamic input activation and an intuition module to enhance learning and adaptability.

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Dynamic Input Activation in Neural Networks for Enhanced Learning and Adaptability

Overview

This repository contains the code and documentation for the project "Dynamic Input Activation in Neural Networks for Enhanced Learning and Adaptability". The project introduces a novel neural network architecture with dynamic input activation and an intuition module to enhance learning and adaptability.

Structure

  • data/: Directory for datasets.
  • runs/: Directory for model checkpoints and logs.
  • src/: Source code directory.
  • notebooks/: Jupyter notebooks for experiments.
  • figures/: Directory for storing figures and plots.
  • docs/: Directory for documentation.
  • README.md: Project description and instructions.
  • requirements.txt: List of dependencies.
  • LICENSE: License file.

Setup

  1. Clone the repository:

    git clone https://github.com/nbursa/Dynamic-Input-Activation-Network.git
    cd Dynamic-Input-Activation-Network
  2. Install the required packages:

    pip install -r requirements.txt
  3. Download the dataset (if applicable) and place it in the data/ directory.

Usage

  1. Train the model:

    python app.py

License

This project is licensed under the MIT License. See the LICENSE file for more details.

About

This repository contains the code and research paper for the project "Dynamic Input Activation in Neural Networks for Enhanced Learning and Adaptability". The project introduces a novel neural network architecture with dynamic input activation and an intuition module to enhance learning and adaptability.

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